AI Analytics Engineer

Job Title: AI Analytics Engineer

Location: Seattle – Eastlake (50% onsite)

Level: Intermediate/Advanced (8+ yrs)

Contract Type: Consulting / Contract 1 yr

JOB DESCRIPTION:

Data Engineering: Python, SQL, Airflow, Spark, dbt, Snowflake/BigQuery, ETL & Orchestration, cloud (AWS, Azure), ERP, Salesforce Data Cloud

Analytics Eng: dbt, SQL Modelling, datamarts, Tableau/PowerBI, metrics definition, Insights and data storytelling, Adobe Analytics

Advanced analytics: Scikit-learn, Tensorflow, Pytorch, MLFlow, feature engineering

AI Tools: OpenAI API, Langchain, Retrieval-Augmented Generation (RAG)

MLOps/Deployment: ML Pipelines, CI/CD, Domino, monitoring/Logging

Job Overview

Bristol Myers Squibb is seeking a highly experienced Senior Analytics Engineer to serve as a key contributor in building advanced analytics infrastructure and AI-driven decision support tools for the Global Patient Operations Cell Therapy team. This role blends data engineering, analytics engineering, and AI/ML integration to enhance visibility into critical operations such as scheduling, clinical trials, and commercial performance.

The ideal candidate thrives in regulated environments, understands the nuances of healthcare data, and can deliver end-to-end from data ingestion through to dashboarding and insight delivery.

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, BigQuery)
• 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, Computer Science preferred)
• Support ad hoc analytics initiatives for clinical trials, commercial ops and digital health systems
• Utilize 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, and 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

Required Qualifications

• 5+ Yrs of experience in data engineering, analytics or applied machine learning
• Strong Python and SQL skills, experience in ETL Orchestration tools (Airflow, Prefect, Domino) ability to manipulate and analyze complex datasets
• Proficiency in modern data stack (dbt, Snowflake/BigQuery, version control, pipelines)
• Experience and familiarity in DataOps/MLOps frameworks, AI/LLM tools 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

Nice to Have

• Knowledge of GxP, HIPAA or compliance standards
• Experience with data modelling in clinical trials, real world evidence (RWE) and 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

Job Type: Contract

Pay: From $100,000.00 per year

Experience:

• OpenAI API, Langchain, Retrieval-Augmented Generation (RAG): 5 years (Required)
• ML Pipelines: 5 years (Preferred)
• Python: 5 years (Preferred)
• SQL: 5 years (Preferred)
• AWS & Azure: 5 years (Preferred)
• Tableau/PowerBI: 5 years (Preferred)

Work Location: In person