Seeking a Machine Learning Scientist II to accelerate drug discovery through advanced analytics and AI, developing predictive models for complex biological and chemical datasets.
Compensation
Base pay salary range for this full-time position for candidates working onsite at our headquarters in Redwood City, CA is listed below. $202,000—$238,000 USD
Responsibilities
Develop, implement, and evaluate machine-learning models that support drug discovery questions including compound activity, selectivity, developability, target engagement, and phenotypic screening outcomes.
Perform exploratory data analysis and quality assessment on chemical, biological, imaging, and phenotypic datasets.
Prepare and integrate heterogeneous datasets including chemical structure and screening data, structural biology outputs, molecular simulation outputs, and high-content imaging or morphological profiling data.
Apply appropriate modeling approaches including supervised learning, deep learning, graph-based methods, and ensemble methods.
Use sound validation strategies to assess model performance, robustness, applicability, and limitations.
Requirements
Ph.D.
M.S.
-Ph.D. in machine learning, computational biology, computational chemistry, computer science, statistics, bioinformatics, or a related quantitative field or M.S. with relevant industry experience.
Providing data analysis and computational support for data-driven efforts to evaluate and improve the MEDLINE indexing product for the National Library of Medicine.
Compensation
The anticipated salary range for this position is $110,000–$135,000 annually.
Responsibilities
Support quantitative analyses evaluating automatic MeSH indexing and its impact on MEDLINE and PubMed users.
Prepare and process PubMed GUI, API, user search and click, bibliographic, indexing, and other relevant datasets for analysis.
Develop and execute scripts for data extraction, cleaning, transformation, aggregation, validation, and analysis using established analytical methods and requirements.
Assist with the development, execution, testing, and maintenance of reproducible data processing and analytical workflows.
Perform exploratory data analysis and apply established statistical and quantitative methods to identify patterns, trends, anomalies, and relationships in data.
An early-career Data Scientist role focused on working with structured and unstructured datasets to discover patterns, develop predictive models, and generate data-driven insights.
Locations (2)
United States
Canada
Responsibilities
Collect, clean, process, and analyze large datasets from multiple sources to identify patterns, trends, and meaningful insights.
Perform exploratory data analysis (EDA) to understand data distributions, relationships, and potential business opportunities.
Develop, train, test, and evaluate machine learning models to solve analytical and predictive problems.
Apply statistical techniques and mathematical methods to interpret data and support evidence-based decisions.
Write efficient code using Python and relevant data science libraries such as Pandas, NumPy, Scikit-learn, and Matplotlib.
Requirements
Master's degree in Data Science
Senior Associate Aws Data Engineer GCC Advisory Gurgaon
Lead the development of advanced machine learning and statistical models to solve complex healthcare problems and design scalable data pipelines for Snowflake/Data Lake platforms.
Responsibilities
Lead the development of advanced machine learning and statistical models
Establish and promote best practices in modeling, experimentation, and analytical rigor
Convert real-world healthcare challenges into scalable data science solutions
Collaborate with global stakeholders to influence product and business strategy
Mentor and enhance the technical capabilities of the data science team
A career within Data & Analytics Services will provide you with the opportunity to help our clients leverage transformation to enhance their customer experiences. The role is a Data Engineer.
Responsibilities
Lead the development of advanced machine learning (ML) and statistical models to solve complex healthcare problems.
Establish and promote best practices in modeling, experimentation, and analytical rigor.
Convert real-world healthcare challenges into scalable data science solutions.
Collaborate with global stakeholders to influence product and business strategy.
Mentor and enhance the technical capabilities of the data science team.
Explore business challenges, develop hypotheses, choose suitable analytical methods, and deliver data-driven solutions
Develop, test, and improve predictive algorithms and artificial intelligence techniques to improve player experiences, engagement, retention, and revenue
Apply statistical analysis, forecasting, predictive modelling, and simulation to understand player behaviour and business performance
Support A/B testing and experiments by selecting relevant metrics, analysing results, and sharing findings that guide business decisions
Create analytical models, simulations, and tools that help teams make informed decisions and find opportunities for improvement
Requirements
MSc or PhD in Data Science, Computer Science, Statistics, Physics, Mathematics, or a related quantitative field, or possessing equivalent experience
A hands-on analytical role with a strong stakeholder focus, turning complex data into meaningful insights that influence business decisions, customer experience, and commercial performance.
Responsibilities
Deliver hands-on analysis using SQL and Python or R, exploring large and complex datasets to uncover trends, investigate business challenges and identify opportunities for improvement.
Partner with business stakeholders to understand their objectives, clarify analytical requirements and translate business questions into structured, meaningful analysis.
Interpret and communicate analytical findings, presenting clear insights and evidence-based recommendations that help stakeholders understand performance and make informed decisions.
Apply exploratory data analysis, statistical techniques and foundational modelling approaches to investigate patterns, understand relationships and support predictive insights.
Collaborate with senior analysts, data scientists, BI developers and data engineers to support analytical projects, insight led data products and the quality and reliability of underlying data.
Partner with business leaders to drive value creation through financial and business leadership, develop long‑range scenario models, and provide financial insights to support strategic decision making.
Responsibilities
Manages a team of financial analysts
Provides functional support to business units
Leverages Financial Centers of Expertise
Partners with senior leadership
Prepares and communicates deliverables to senior management and Board of Directors
Requirements
Bachelor’s degree in Business, Finance, Accounting or related field
Nice to have: Master’s degree in Business, Finance, Accounting or related field
Partner with business leaders to drive value creation through financial and business leadership, develop long‑range scenario models, and provide financial insights to senior management and the Board of Directors.
Responsibilities
Manage a team of financial analysts
Provide functional support to business units
Leverage Financial Centers of Expertise for insights
Partner with senior leadership for resource allocation
Prepare and communicate deliverables to senior management and Board
Requirements
Bachelor’s degree in Business, Finance, Accounting or related field
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