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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - **Company:** Net2Source - **Location:** United States (Remote available) - **Experience:** Experienced - **Contract:** Temporary contract - **Skills:** Amazon Web Services, Data Analysis, Continuous Integration, Python (Programming Language), Machine Learning, Natural Language Processing, Power BI, Azure Machine Learning, SQL Databases, Tableau (Software), Feature Engineering, Data Ingestion, Large Language Models, Prompt Engineering, Deep Learning, Electronic Medical Records, Generative AI, Containerization, Core Data, Information Technology, Data Management, Machine Learning Operations, Restful APIs, Api Management, Docker, Databricks - **Published:** June 16, 2026 - **Apply:** https://arc.dev/remote-jobs/j/net2source-n2s-data-scientist-oxab59wluq ## About the Role * Master's Degree with 5-7+ years of experience OR PhD with 3-5+ years of experience. * Degree must be in Data Science, Computer Science, Statistics, Operations Research, Mathematics, or a related quantitative discipline. * Experience must be in data science, machine learning, or advanced analytics. * Preferred: Pharmaceutical/life sciences commercial analytics or healthcare consulting experience. Technical Skills & Stack * Core DS: Python (preferred) or R; SQL; Supervised/Unsupervised ML algorithms; Statistical analysis and experimental design. * GenAI Stack: Hands-on experience with LLMs, Prompt Engineering, RAG architecture, and Agent-based AI systems (LangChain, MCP, A2A, AutoGen). Familiarity with Vector databases, embeddings, and API integrations. * MLOps & Infra: Experience with pipeline deployment and monitoring using Databricks, Azure ML, or AWS SageMaker. Knowledge of REST APIs, containerization (Docker), and CI/CD pipelines. * Visualization: Ability to build demo apps in Databricks; proficiency with BI tools (Power BI, Tableau); strong storytelling skills. ## Description We are seeking a highly motivated Data Scientist to join a top-tier pharmaceutical client's Global Data & Digital Innovation (GDDI) organization. This role bridges advanced machine learning, GenAI agent development, and production-grade MLOps pipelines to deliver actionable insights across Sales, Marketing, and Advanced Analytics teams. Domain Expertise Required : This role focuses entirely on the Pharmaceutical Commercial Domain, combining advanced machine learning, GenAI agent development, and production-grade MLOps pipelines to drive commercial effectiveness across Sales, Marketing, and Advanced Analytics., Core Data Science & Commercial Strategy * Predictive Modeling: Develop and deploy models for patient events (line switches, initiation) and patient journey/longitudinal data analysis. * Next Best Action (NBA): Scale NBA solutions to optimize multichannel HCP engagement and segmentation. * Advanced ML: Apply regression, classification, and NLP techniques for commercial effectiveness. * Marketing Analytics: Create multi-touch attribution pipelines for customer journeys and promotional response modeling. * Stakeholder Support: Partner with Sales, Marketing, and Analytics teams to translate complex business problems into analytical solutions. GenAI Integration * Integrate GenAI capabilities into commercial workflows (HCP engagement planning, content personalization, and GenAI interfaces for ML pipelines). ML Engineering & MLOps * End-to-End Pipelines: Oversee build/maintenance of pipelines (data ingestion, feature engineering, training, evaluation, and deployment). * MLOps Best Practices: Implement model versioning, monitoring, retraining, and CI/CD integration. * Data Platforms: Work with large-scale healthcare datasets (Claims, EHR/EMR, CRM, digital engagement data) ensuring HIPAA compliance. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [REST, GraphQL, gRPC, and more: A comparison of modern API styles](https://www.wearedevelopers.com/videos/100247-rest-graphql-grpc-and-more-a-comparison-of-modern-api-styles) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Data Analytics with Microsoft Fabric: End-to-End Use Case with Data Agents](https://www.wearedevelopers.com/videos/1547-data-analytics-with-microsoft-fabric-end-to-end-use-case-with-data-agents) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) ## Related Articles - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)