Verified Job On Employer Career Site Job Summary: Flagship Pioneering is a venture capital firm that invests in life sciences and healthcare companies. As a Data Scientist at Lila Sciences, you will transform complex datasets into actionable insights to drive decision-making in an autonomous lab, collaborating with various specialists to ensure data quality and build predictive models. Responsibilities: • Design and maintain robust ETL pipelines to ingest, validate, and preprocess data from diverse sources—electrochemical tests, materials characterization, and automated lab instruments. • Perform domain-relevant data transformations, extract meaningful descriptors from raw data (e.g., voltage curves, spectroscopic signatures, image-based measurements) and develop statistical or machine learning models to relate independent variables (time, composition, etc.) to performance metrics and failure modes. • Create interactive dashboards and reports to communicate trends, anomalies, and key insights to scientific and engineering teams. • Collaborate with ML scientists to integrate your analytical outputs into active learning loops, helping to prioritize experiments and optimize resource allocation. • Work closely with R&D leadership, Product Managers, and automation specialists to translate scientific questions into data requirements and modeling strategies. • Establish best practices for code versioning, data provenance, and analysis notebooks; contribute to internal knowledge bases and publications. Qualifications: Required: • Master’s or Ph.D. in Data Science, Statistics, Materials Science, Chemistry, Physics, or a related quantitative field. • 2 years of experience in data analysis, statistical modeling, or machine learning—ideally applied to physical sciences or engineering datasets. • Proficiency in Python (pandas, NumPy, scikit-learn) and SQL for data manipulation and analysis. • Hands-on experience building ETL workflows using tools like Airflow, Prefect, or similar. • Strong foundation in experimental design, statistical inference, and multivariate analysis. • Familiarity with data visualization libraries (Plotly, Dash, or similar) and dashboard frameworks. Preferred: • Experience working with electrochemical or materials characterization data (e.g., impedance spectroscopy, X-ray diffraction, electron microscopy). • Materials-specific python libraries (pymatgen) • Exposure to cloud-based data platforms (AWS, GCP, or Azure) and scalable storage solutions. • Knowledge of containerization (Docker, Singularity) and workflow orchestration (Snakemake, Nextflow). • Prior contributions to open-source data tools or scientific software. • Understanding of active learning, Bayesian optimization, or uncertainty quantification in experimental contexts. Company: Flagship Pioneering is a venture capital firm that invests in life sciences and healthcare companies. Founded in 2000, the company is headquartered in Cambridge, Massachusetts, USA, with a team of 501-1000 employees. The company is currently Late Stage. Flagship Pioneering has a track record of offering H1B sponsorships.