Senior Analytics Engineer

About the Role

Key Responsibilities

• Design and build scalable data pipelines using python, SQL and cloud-based tools (Azure, AWS).
• Develop and maintain analytics models and data transformation using dbt, airflow and data warehouses (ex: Snowflake, Big Query).
• Build and manage dashboards and data visualizations using web-based tools, Tableau, Power BI.
• Ensure data quality, governance and security compliance across engineering workflows.
• Responsible for ingestion, integration and delivery of data products and insights across multiple platforms applying and maintaining data integrity and governance rules.
• Knowledge of deep learning methods for NLP (quantitative area of study, Comp Science preferred).
• Support ad hoc analytics initiatives for clinical trials, commercial ops and digital health systems.
• Utilizes supervised or unsupervised methods, learning from vast amounts of unlabeled data to drive insight.
• Experience working with unstructured text.
• Develop high quality analytical and statistical models, insights, patterns, visualizations, that can be used to improve decision making in manufacturing operations.
• Responsible for documentation of all technical work both within and outside of formal document management systems.

Requirements

• 5+ years of experience in data engineering, analytics or applied machine learning.
• Strong python and SQL skills, experience in ETL orchestration tools (Airflow, Prefect, Domino) and ability to manipulate and analyze complex datasets.
• Proficiency in modern data stack (dbt, Snowflake/Big Query, version control, CI/CD pipelines).
• Experience and familiarity with DataOps/MLOps frameworks, AI/LLM tooling such as OpenAI, LangChain, Hugging Face Transformers.
• Strong communication and stakeholder engagement skills.
• Experience in regulated industry (Pharma, biotech or life sciences) is highly preferred.
• Solid grasp of data science fundamentals: causal inference, regression, classification, experimental design.
• Knowledge of data engineering tools: Python, SQL, Airflow, Spark, Dbt, Snowflake/Big Query, Cloud (AWS, Azure).
• Experience with analytics tools: SQL Modelling, DataMart, Tableau/Power BI, metrics definition, insights and data storytelling.
• Experience with advanced analytics: Scikit-Learn, TensorFlow, PyTorch, MLflow, Feature Engineering.
• Familiarity with AI tools: OpenAI API, LangChain, Retrieval-Augmented Generation (RAG).
• Experience with MLOps/Deployment: ML Pipelines, CI/CD, Domino, monitoring/Logging.

Nice to Have

• Knowledge of GxP, HIPAA or compliance standards.
• Experience with data modelling in clinical trials, real world evidence (RWE) or commercial analytics.
• Familiarity with NLP, time series forecasting, or image analytics in healthcare.
• Master's Degree or PhD in Public Health, Economics, Statistics, Computer/Data Science, or related field.

Qualifications

• Educational background not explicitly specified, but advanced degrees preferred for some qualifications.

Benefits & Perks

• 401k Retirement Savings Plan administered by Merrill Lynch
• Commuter Check Pretax Commuter Benefits
• Eligibility to purchase Medical, Dental & Vision Insurance through ECLARO