Join Mithrl as a Lead Bioinformatics EngineerAt Mithrl, we envision a future where groundbreaking medicines are swiftly delivered to patients, transforming the landscape of health care.Mithrl is pioneering the world's first commercially available AI Co-Scientist, a revolutionary discovery engine that converts complex biological data into actionable insights in mere minutes. By simply asking questions in natural language, scientists receive immediate responses with comprehensive analyses, innovative targets, hypotheses, and patent-ready reports.Our impressive growth trajectory includes:12X year-over-year revenue growthTrusted by top-tier biotech firms and major pharmaceutical companies across three continentsFacilitating real breakthroughs from target discovery to patient outcomes.About the RoleWe are in search of an innovative Lead Bioinformatics Pipeline Engineer to architect and expand Mithrl’s multimodal scientific processing pipelines. You will be responsible for developing workflows that convert raw biological data into clean, reproducible outputs that fuel Mithrl’s AI Co-Scientist. Your work will encompass a range of modalities including microarray, imaging, spatial transcriptomics, genomics, epigenomics, flow cytometry, and more.This pivotal role lies at the core of our technical infrastructure. You will design Nextflow and nf-core style pipelines, implement modality-specific validation and quality control layers, and collaborate closely with our Tabular Data Team and Knowledge Curation Team to ensure seamless data harmonization, variable ID mapping, and schema alignment. Your contributions will enable scientists to pose inquiries and receive accurate, data-driven answers instantaneously.If you are passionate about constructing robust scientific workflows and tackling high-impact challenges, you will find your place here.

ABOUT MITHRLAt Mithrl, we envision a future where innovative medicines are delivered to patients in mere months instead of years, and where scientific advancements occur at the speed of thought.We are pioneering the world's first commercially available AI Co-Scientist, a transformative discovery engine that rapidly converts complex biological data into actionable insights. Scientists can pose inquiries in natural language, and Mithrl provides comprehensive analyses, novel target suggestions, hypotheses, and patent-ready documentation.Our impressive growth reflects our success:Achieved 12X year-over-year revenue growthTrusted by leading biotech companies and major pharmaceutical firms across three continentsFacilitating significant breakthroughs from target discovery to patient outcomes.ROLE OVERVIEWWe are searching for a QA Engineer specializing in Scientific Software to develop the testing, validation, and monitoring infrastructure that ensures the accuracy and reliability of the Mithrl AI Co-Scientist. This position necessitates a PhD-level scientist or computational biologist who comprehends the intricacies of the drug development lifecycle and possesses practical experience with omics data. A solid scientific foundation is crucial for assessing the biological relevance of Mithrl's outputs.In this role, you will implement automated testing for analysis workflows, data ingestion pipelines, and discovery applications. You will establish CI systems for early regression detection, set up monitoring and alerting for system performance, and ensure every module in Mithrl generates scientifically valid and reproducible outputs. This position is a vital link between scientific knowledge and software quality engineering, essential for maintaining trust in Mithrl's analytical capabilities.If you are a scientist passionate about product reliability, reproducibility, and the validation of machine learning-powered scientific tools, this role offers a uniquely impactful opportunity.KEY RESPONSIBILITIESDevelop automated testing frameworks for data ingestion, analysis modules, discovery applications, and new product features.Create scientific validation frameworks to ensure correctness and reproducibility of machine learning-driven biological analyses.Implement continuous integration workflows that conduct end-to-end tests with every commit, identifying scientific and computational regressions.Establish monitoring and alerting systems to track health, performance, and reliability metrics.

Bioinformatics Engineer - Spatial AIJoin LatchBio, where our innovative AI agents empower over 4,000 scientists to effectively analyze and interpret complex data generated from cutting-edge spatial and multi-omic tools within the biotech industry.We are on the lookout for proficient bioinformatics engineers with a robust background in both computational and experimental aspects of spatial biology. Your role will be pivotal in shaping the future of agentic analysis tools.Your ResponsibilitiesLead comprehensive spatial transcriptomics analyses for various projects, from processing raw platform outputs to quality control, cell segmentation, cell typing, differential expression/enrichment, and spatial inference, ultimately substantiating biological claims.Develop reproducible workflows that provide transparent decision traces detailing filters applied, rationale behind them, and factors that could alter conclusions.Engage in advanced spatial reasoning techniques beyond standard clustering, focusing on neighborhood and adjacency enrichment, spatial gradients, spatial differential expression, and analyses that account for spatial autocorrelation.Tackle platform and data challenges with accuracy, transforming ambiguous results into clear hypotheses, conducting sanity checks, and creating systematic debugging plans.Essential QualificationsProven experience in end-to-end data analysis using one or more spatial technologies such as Seeker, Trekker (Slide-seq), MERFISH, DBiT-seq, Xenium, Visium, Stereo-seq, GeoMx, CosMx, or equivalent assays.Experience analyzing 3 or more datasets from raw data to actionable insights for publications or industry-related experiments.Strong understanding of kit-specific quality control thresholds and the ability to discern meaningful numerical outcomes.Familiarity with computational biology tools tailored for spatial tasks, such as cell segmentation, cell typing, and ligand-receptor interaction analysis.Preferred QualificationsPublished work utilizing contemporary spatial biology methodologies.Experience in developing tools or software packages for spatial biology applications.Background in generating training data for AI agents or foundational models.Who You AreYou are a scientifically adept engineer who seamlessly integrates experimentation with computational analysis. You embrace the possibility of being incorrect, adapt your views based on evidence, and document your decisions to enable reproducibility and constructive critique. Your communication skills are exceptional, and you are committed to maintaining the integrity of your work.

Join the Prima Mente TeamAt Prima Mente, we are at the forefront of biology and artificial intelligence. Our innovative lab is dedicated to generating unique data, creating versatile biological foundation models, and translating groundbreaking discoveries into both research and clinical applications. Our primary focus is on unraveling the complexities of the brain to enhance its health, safeguard it against neurological disorders, and foster cognitive enhancement. Our diverse team of AI researchers, experimentalists, clinicians, and operations experts spans across London, San Francisco, and Dubai.Position Overview - Multi-omicsIn this role, you will be instrumental in formulating and questioning significant biological hypotheses aimed at discovering biomarkers and targets pertinent to neurological diseases.Key Responsibilities:Conduct feature engineering and prepare datasets for machine learning applications and foundational AI model training.Analyze in-house wet lab experiments to develop proprietary methods and generate data for our models.Build and optimize multi-omic bioinformatics pipelines.Establish and manage collaborative research initiatives with academic and industry partners focused on Alzheimer's disease biology.Growth ExpectationsWithin 1 month: You will independently manage your own analyses and experiments using our cloud computing environment, creating bespoke workflows to efficiently process data.Within 3 months: Your research will be seamlessly integrated into our AI models.Within 6 months: Your pipelines will be running in automated production, contributing to daily AI model training. You will collaborate closely with AI/ML engineers and lab scientists, leading the technical aspects of external partnerships.Who You AreYou aspire to push the boundaries of what is achievable at the intersection of AI and biology. You possess experience in deriving novel biological insights from multi-omic, multi-modal datasets, along with a track record of top-tier publications and/or patents.We understand that not every candidate will meet every qualification. We encourage strong applicants to apply, even if they specialize in certain areas and wish to expand their expertise in others.Preferred Qualifications:Practical experience in generating insights from biological datasets (genomics, epigenetics, transcriptomics, proteomics, ATAC-Seq).Proficient software engineering skills, including the ability to write high-quality code for operational purposes.

Join Prima Mente: A Leader in Biology AIAt Prima Mente, we are redefining the frontier of biology through artificial intelligence. Our mission is to generate unique datasets, develop versatile biological foundation models, and translate groundbreaking discoveries into impactful research and clinical outcomes. With a commitment to understanding the complexities of the brain, we aim to shield it from neurological diseases while enhancing overall health. Our diverse team of AI researchers, experimentalists, clinicians, and operational experts operates across London, San Francisco, and Dubai.Role Overview: GPU/CPU-Accelerated BioinformaticsWe are seeking a skilled Bioinformatics Software Engineer to architect and implement scalable production pipelines for processing multi-omics data. The successful candidate will enable rapid transitions from hypothesis to patent-ready solutions in a matter of months.Key Responsibilities:Design and implement bioinformatics pipelines optimized for GPU/CPU utilization utilizing tools like Flyte and Nextflow, capable of processing over 1,000 samples at scale.Optimize performance and cost efficiency by leveraging GPU/CPU acceleration where it provides the greatest benefit.Collaborate with experimental and machine learning teams to validate computational results and align processing with model requirements.Foster and manage collaborations with academic and industrial research partners.Growth Expectations1 Month: You will be deploying your workflows on GPU/CPU-accelerated cloud infrastructure to process multi-omic experiments, while building relationships with AI/ML and wet lab teams to understand their requirements.3 Months: Your optimized pipelines will be processing thousands of samples with substantial speed enhancements and reduced costs, yielding publication and patent-ready outcomes.6 Months: Your automated pipelines will support daily AI model training, and you will co-design experiments alongside AI/ML engineers, leading technical execution on external collaborations.Your ProfileYou are passionate about pushing the boundaries of AI and biology. As an engineer rather than an analyst, you thrive on enhancing performance and efficiency while architecting robust systems. You are comfortable making rapid technical decisions and iterate quickly.Desired QualificationsExperience in bioinformatics, computational biology, or a related field.Proficiency in software engineering, particularly in developing scalable data processing pipelines.Strong understanding of multi-omics data and methods.Familiarity with GPU/CPU acceleration techniques.Excellent communication and collaboration skills.

About Arena IntelligenceArena Intelligence serves as the premier platform for assessing the effectiveness of AI models in practical applications. Founded by a team of researchers from UC Berkeley’s SkyLab, our mission is to push the boundaries of AI measurement and utilization in real-world scenarios.Every month, millions of users engage with Arena Intelligence to investigate the performance of cutting-edge systems. We actively incorporate feedback from our community to enhance our model evaluations, ensuring they are transparent, rigorous, and centered around human values. Leading organizations and AI research facilities rely on our assessments to gauge real-world reliability, alignment, and impact. Our leaderboards are recognized as the benchmark for AI performance, trusted by industry leaders and influencing global discussions on model reliability and advancement.Our diverse team includes researchers, engineers, academics, and innovators from renowned institutions such as UC Berkeley, Google, Stanford, DeepMind, and Discord. We prioritize truth, agility, and craftsmanship, valuing curiosity and impact over traditional hierarchies. At Arena, we foster an environment where insightful and inquisitive individuals from varied backgrounds can excel. Each team member is a specialist in their area, contributing to a culture of excellence and focus.About the RoleWe are looking for a Scientific Content Lead to uphold and articulate the scientific integrity of the most reliable AI evaluation platform globally. In this role, you will ensure that Arena’s methodologies, data quality standards, and evaluation outcomes are effectively communicated to researchers, labs, policymakers, analysts, and businesses.This position is highly technical and demands cross-functional collaboration. You will collaborate with our research team to translate evaluation science into precise public content, preemptively address methodological criticisms, and maintain Arena’s dedication to transparency and impartiality.Your ResponsibilitiesDevelop and manage Arena’s scientific communications strategy, ensuring that our evaluation methodologies, benchmarks, and data quality practices are accurately represented externally.Steer Arena’s proactive narrative regarding data quality, countering common criticisms and misconceptions with transparency, evidence, and integrity in storytelling.Create foundational explanations of Arena’s measurement strategies, including methods like Bradley-Terry-Luce ranking, confidence intervals, and uncertainty-aware interpretations.Ensure responsible communication of Arena’s leaderboards, clarifying that rankings are statistical estimates, small variances may be noise, and uncertainty must be accounted for in public interpretations.Engage with various stakeholders to foster a deeper understanding of Arena’s scientific contributions and methodologies.

Join Prima Mente as a Bioinformatics EngineerAt Prima Mente, we are pioneers in the field of biology and artificial intelligence. Our mission is to generate novel data, create versatile biological foundation models, and turn groundbreaking discoveries into impactful research and clinical applications. Our primary focus is on understanding the human brain—protecting it from neurological diseases while enhancing its capabilities for better health. With teams located in London, San Francisco, and Dubai, we are committed to pushing the boundaries of AI and biology.Role Overview - Multi-omicsAs a Bioinformatics Engineer, you will play a crucial role in formulating and testing significant biological hypotheses aimed at discovering markers and targets related to neurological disorders.Key Responsibilities:Develop multi-omic bioinformatics pipelines.Conduct feature engineering and prepare datasets for downstream machine learning, foundational AI training, and applications.Analyze in-house wet lab experiments to create proprietary methods and data for our models.Growth ExpectationsWithin 1 month: You will manage your analyses and experiments using our cloud computing environment, developing workflows to process your data efficiently.Within 3 months: You will independently own and optimize an analysis or data processing pipeline, producing results suitable for patenting and publication.Within 6 months: You will have integrated your research findings into our AI models.Who You AreYou are eager to redefine the possibilities at the intersection of AI and biology. You possess experience in deriving insights from multi-omic and multi-modal data, contributing to top-tier publications.We understand that not every candidate will meet all the criteria. Ideal applicants will have strengths in some areas and a desire to develop in others.Ideal Qualifications:Experience generating insights from biological datasets (including genomics, epigenetics, transcriptomics, proteomics, and ATAC-Seq).Strong software engineering skills, with the ability to produce high-quality code that supports our software infrastructure.Familiarity with data wrangling, engineering, analysis, and visualization libraries in Python or Julia, as well as frameworks like Spark, Hadoop, and NoSQL.

Role Overview LatchBio is hiring a Bioinformatics Engineer focused on Single-Cell AI in San Francisco. This role centers on applying artificial intelligence to single-cell genomics data, with the goal of advancing personalized medicine. What You Will Do Analyze single-cell genomics datasets using AI methods Work with teams from different scientific backgrounds to build bioinformatics solutions Help uncover new insights into complex biological systems

Thank you for your interest in joining Uncountable Engineering!Uncountable is on the lookout for recent graduates eager to embark on a career in data engineering, focusing on the management of customer datasets. Our mission is to transform industrial research and development. We are in search of driven software engineers who can contribute to the creation of tools designed to expedite the development of new chemicals and materials.Your key responsibilities will include structuring and ingesting customer data into the Uncountable Web Platform, where scientists input and analyze their experimental data. In this role, you will (1) manipulate, transform, and upload R&D data using Python scripts; (2) establish ETL pipelines between Uncountable and customer data warehouses; (3) devise innovative solutions for users to import and export their data. This position requires a creative, analytical thinker with excellent cross-functional communication skills and the capability to analyze large datasets, identifying necessary steps to clean, process, and upload the data onto our platform.

Databricks is seeking an experienced Engineering Manager to lead our Pipelines Engine team. In this role, you will oversee the development and optimization of our data pipeline infrastructure, ensuring that we deliver high-performance solutions that meet the needs of our clients. You will collaborate with cross-functional teams to drive innovation and maintain our leadership in the data analytics space.

Join Veracyte, a leader in transforming cancer care through innovative diagnostics that empower patients and clinicians alike. At Veracyte, we provide an inspiring work environment where you can make a significant impact on patients' lives while advancing your career. Our culture, known as the Veracyte way, emphasizes collaboration, resilience, and a commitment to excellence.Our Core Values:We Seek A Better Way: We boldly innovate and learn from challenges to improve cancer care.We Make It Happen: We prioritize urgency, quality, and enjoyment in our work.We Are Stronger Together: We foster open collaboration and celebrate our collective successes.We Care Deeply: We honor our diverse backgrounds and support each other in doing what is right.The Role:We are on the lookout for an enthusiastic Bioinformatics Research Scientist to join our Translational Bioinformatics group within the Bioinformatics and Data Science Team. This pivotal role involves leveraging computational and statistical techniques on extensive transcriptomic and genomic datasets, particularly focusing on prostate cancer biology and its clinical implications. The ideal candidate will play a key role in identifying clinically relevant molecular signatures that enhance disease stratification, prognosis, and the development of diagnostics, while effectively communicating findings to both scientific and clinical audiences. This position offers a unique opportunity to bridge the realms of data science, biology, and clinical research through close collaboration with scientists, clinicians, and cross-functional teams to convert complex data into actionable insights.

About Stand Insurance Stand Insurance is rethinking how property risks are understood and managed. By combining advanced physics with artificial intelligence, the team models catastrophic risks at the asset level and automates underwriting and risk mitigation before losses happen. Instead of simply delivering insurance, Stand builds a scalable risk engine that aims to deliver real-world impact and stay in markets where others exit. Traditional property insurance often relies on outdated data and manual workflows, accepting damage as a given. Stand takes a different path: simulating real-world catastrophes for individual properties, turning those simulations into actionable steps, and automating operations around those insights. The result is a platform that can underwrite risks others avoid, while reducing operational friction. Role Overview: Machine Learning Engineer – Data Pipeline This role centers on building and maintaining the tools behind Stand’s data annotation pipeline. Areas of focus include computer vision, human-in-the-loop management, quality assurance, and economic optimization. The main goal: increase automation and lower cost-per-policy, while keeping quality high. Early on, work will involve hands-on management of the pipeline, quality checks, and close coordination with the annotation team. As experience grows, the focus will shift to developing advanced data science and machine learning systems, especially around quality instrumentation, automated QA, predictive labeling, and computer vision models. Over time, the role will evolve into shaping a systems-driven, automation-focused framework for the entire annotation lifecycle. Key Responsibilities Pipeline Operations and Reliability Monitor and maintain the daily health of the annotation pipeline Set up escalation protocols and frameworks for categorizing failures Lead the transition from manual to automated operations Quality Instrumentation Design validation systems that align with downstream model metrics Develop anomaly detection models for annotation workflows Automate tasks to cut down on manual QA effort Vendor and Annotator Performance Define and track performance metrics for vendors and annotators Location San Francisco

About Our Organization:Welcome to Scribd Inc. (pronounced “scribbed”), where our passion lies in igniting human curiosity through storytelling and knowledge-sharing. We invite you to join our dynamic team as we work towards democratizing the exchange of ideas and empowering collective expertise with our innovative products: Everand, Scribd, Slideshare, and Fable.This job posting represents an established opportunity within our organization.At Scribd, we cultivate a culture where authenticity and boldness thrive. We value open discussions and commitment as we embrace the unexpected, empowering every employee to take initiative while keeping our customers at the forefront.We believe in a balanced approach to work structure, merging individual flexibility with community engagement. Our Scribd Flex program allows employees, in collaboration with their managers, to choose work styles that best suit their needs. This initiative emphasizes the importance of intentional in-person gatherings to foster collaboration and connection. Thus, occasional in-person attendance is a requirement for all Scribd employees, regardless of their remote status.What do we seek in our new teammates? We prioritize candidates who embody “GRIT” – a blend of passion and perseverance towards long-term goals. At Scribd, we encourage a GRIT-driven approach to work, where the ability to set and achieve Goals, deliver Results, contribute Innovative ideas, and positively impact the Team through collaboration is essential.About the Team:Our ML Data Engineering team is at the forefront of metadata extraction, enrichment, and content understanding across all Scribd products. We manage vast volumes of documents and images, ensuring high-quality metadata that enhances content discovery and builds trust among millions of users around the globe.Our systems function on a massive scale, incorporating diverse datasets like user-generated content, ebooks, audiobooks, and more. We operate at the convergence of machine learning, data engineering, and distributed systems, working closely with applied research and product teams to deploy scalable ML solutions.

At Scribd, Inc., we aim to enhance human understanding. Our innovative products—Scribd®, Slideshare®, Everand™, and Fable—empower billions globally to not just access knowledge, but also to apply it and achieve expertise.Company CultureWe foster an environment where our employees can be authentic and courageous, engaging in constructive debates while embracing unexpected challenges. Every team member is encouraged to take initiative, prioritizing customer needs.We understand that optimal performance arises from a mix of personal flexibility and meaningful community interaction. Our Scribd Flex program allows team members to choose their working style and location, while still emphasizing in-person collaborations that enrich our culture. Attendance at occasional in-person events is necessary for all employees, regardless of their location.We seek team members who embody “GRIT”—a blend of passion and perseverance towards long-term objectives. This ethos informs our approach to setting and achieving Goals, delivering impactful Results, fostering Innovation, and enhancing our Team dynamics through collaboration.This posting represents an open position within our organization.About Our Team:Our ML Data Engineering team is responsible for metadata extraction, enrichment, and content comprehension across all Scribd offerings. We handle hundreds of millions of documents and billions of images, providing high-quality metadata to facilitate content discovery and trust for millions of users worldwide.Operating at a massive scale, our systems support diverse datasets, including user-generated content (UGC), ebooks, audiobooks, and more. We collaborate closely with applied research and product teams to deploy scalable machine learning and large language model (LLM)-powered solutions in production.Role Overview:We are looking for a Software Engineer II with robust backend development expertise and a keen interest in addressing complex data challenges at scale. You will design, build, and optimize distributed systems that extract, enrich, and process metadata for a variety of content. This role involves close collaboration with ML engineers, product managers, and cross-functional teams.

At worldlabs, we are pioneers in building foundational world models that possess the ability to perceive, generate, reason, and interact seamlessly with the 3D environment. Our mission is to unlock the full potential of AI through spatial intelligence, transforming perception into action and imagination into reality.We envision that spatial intelligence will revolutionize storytelling, creativity, design, simulation, and immersive experiences in both the virtual and physical realms.We are proud to bring together a world-class team driven by curiosity and passion, with diverse backgrounds in technology—from AI research to systems engineering and product design—creating a dynamic feedback loop between our innovative research and user-centric products.Role OverviewWe are in the process of developing a robust web application focused on 3D Gaussian Splat scene generation, editing, and publishing. We seek a Pipeline Engineer who will integrate cutting-edge research features, ensuring they are reliable, debuggable, and user-friendly.This role is characterized by a high level of ownership and is primarily backend-focused, bridging the gap between R&D and frontend. You will engage end-to-end with graphics/ML algorithms, backend services, and frontend UI, transforming proof-of-concepts into dependable features. We are looking for someone who thrives on making complex systems operate smoothly in production and continuously refines them based on both internal evaluations and user feedback.

Benchling creates software tools for scientists and biotech companies, supporting research and development across the globe. The platform serves more than 200,000 scientists, including teams at organizations like Sanofi and Moderna, as well as academic research labs. By connecting experiments, structured data, and AI-powered insights, Benchling works to reduce the time it takes for discoveries to reach real-world applications. Role overview This Software Engineer position focuses on integrating advanced scientific AI models into the Benchling platform. The main responsibility is to build a scalable system for hosting and managing scientific models, while also developing frameworks that allow model creators to bring their solutions into the Benchling environment. What you will do Develop and maintain a platform that supports scientific AI models at scale. Create frameworks that make it easier for model developers to contribute to Benchling. Experiment with new technologies to improve model integration and performance. Work closely with internal teams and external partners to deliver solutions. Help shape how scientists design molecules and apply AI in their research workflows. Location This role is based in San Francisco, CA.

Thank you for your interest in joining the Uncountable Engineering team!Uncountable is on the lookout for enthusiastic recent graduates eager to embark on a data engineering career focused on managing customer datasets. Our mission is to transform the landscape of industrial research and development. We seek driven software engineers to develop tools that expedite the creation of new chemicals and materials.In this pivotal role, you will structure and ingest customer data into the Uncountable Web Platform, where scientists conduct and analyze their experiments. Your responsibilities will include (1) manipulating, transforming, and uploading R&D data using Python scripts, (2) establishing ETL pipelines between Uncountable and various data warehouses utilized by our customers, and (3) devising innovative solutions for users to import and export their data. This role requires a creative and analytical mindset, strong cross-functional communication skills, and the ability to sift through large datasets to identify necessary steps for data cleaning, processing, and uploading onto our platform.

Uncountable is on the lookout for a passionate Scientific Implementation Associate to integrate science and data into impactful business development. This dynamic role is pivotal in bringing scientists and their research into the Uncountable ecosystem.As an Implementation Associate, you will support both existing and new customers with their implementation initiatives. Your responsibilities include restructuring and contextualizing customer data, designing data structures within Uncountable, and configuring our platform to deliver value across various organizational levels. This role requires a passion for data and materials science, coupled with strong communication and time management skills, enabling you to empathize with a diverse range of users in the R&D landscape.In your first month, you will begin restructuring customer data to support ongoing initiatives, collaborating with our account management team to accurately configure experiments within the platform for scientists.By the end of your third month, you will take charge of leading implementation projects for existing customers, facilitating meetings, collaborating on timelines and deliverables, and ensuring successful new usage within our platform.After six months, you will own the implementation process for a new customer, leading demonstrations, orchestrating meetings, setting timelines, and advocating for product development that addresses the unique needs of our most exciting customers.

Uncountable is on the lookout for a talented Scientific Implementation Manager who possesses a diverse range of scientific expertise and is eager to transition into a role focused on business development. This position plays a pivotal role in integrating scientific solutions into the Uncountable ecosystem, ensuring that both scientists and their research benefit from our innovative platform.As a Scientific Implementation Manager, your responsibilities will include: (1) Supporting new business development efforts, (2) Leading the implementation of scientific solutions, (3) Restructuring and contextualizing customer data, and (4) Utilizing real-world customer insights to inform product development, thereby enhancing our data structuring tools designed for R&D. This is a dynamic, project-driven role that involves collaboration with customers and engineering teams. The ideal candidate will exhibit a comprehensive understanding of scientific principles, exceptional communication skills, and the capability to empathize with diverse users within the R&D landscape.Within the first 30 days, you will become proficient in understanding and processing new sales leads and onboarded customers. You will collaborate closely with the customer success and sales teams to accurately configure experiments within our platform tailored to the end-users' needs.By the 60-day mark, you will begin leading meetings and demonstrations with existing and prospective customers, conducting scientific due diligence, gathering new data, and iterating on platform configurations in conjunction with clients.Within 90 days, you will assume full responsibility for the implementation process for new and prospective clients. This includes leading demonstrations, orchestrating meetings, setting timelines, and advocating for product development that meets the unique requirements of our most exciting customers.Salary: $90,000 - $120,000 per year, in addition to performance bonuses and equity opportunities.Qualifications and SkillsMaster's degree or at least 3 years of experience in a scientific field such as chemistry, biology, materials science, chemical engineering, or related disciplines.Strong proficiency in data handling, particularly with Excel; knowledge of Python or other programming languages is advantageous.Ability to effectively communicate complex technical concepts in a clear and comprehensible manner.