> Markdown version of [/jobs/ext/192506-lead-data-scientist](https://www.wearedevelopers.com/jobs/ext/192506-lead-data-scientist). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Data Scientist - **Company:** DRML HOLDINGS LLC - **Location:** United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** A/B Testing, Artificial Intelligence, Amazon Web Services, BigQuery, Data Warehousing, EHealth, Python (Programming Language), Machine Learning, Azure Machine Learning, Feature Engineering, Sql Optimization, Large Language Models, Snowflake, Prompt Engineering, Machine Learning Operations, Databricks - **Published:** May 21, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=c7979c24c8808c1b ## About the Role Do you have experience in Tooling?, Do you have a Bachelor's degree?, This role is best suited for individuals who thrive in a fast-paced, entrepreneurial environment and bring a proven track record of delivering results through strong partnership and influence. * Vision - the ability to zoom out, define what "good" looks like, and clearly communicate that direction across and beyond the organization. * Strategic problem solving - the ability to translate vision into action by breaking complex opportunities or challenges into simple, executable strategies. * Grounded Leadership - the ability to lead with confidence in direction while demonstrating humility in execution, taking ownership, seeking input, and adapting as new information emerges. * Accountability and collaboration - the ability to take ownership of outcomes while motivating others to work effectively across the organization and setting clear expectations. * Grit - the willingness and ability to overcome challenges, move beyond ideas, and consistently drive results., Applicants must be legally authorized to work in the United States. HCEsquared® does not sponsor or assume sponsorship of employment visas., * Demonstrated leadership essentials as described above * 4-year degree from an accredited academic institution * 5+ years in applied data science, ML engineering, or a closely related quantitative field, with production models deployed - not just research prototypes * Production-quality Python and advanced SQL; hands-on experience with a modern cloud data warehouse at scale (e.g., Snowflake, BigQuery, Databricks) * Experience deploying models on a major cloud ML platform (e.g., AWS SageMaker, GCP Vertex AI, Azure ML) and working with modern ML tooling - feature stores, experiment tracking, model registries, A/B testing, and production monitoring * Hands-on experience applying LLMs and generative AI - prompt engineering, structured extraction, RAG, or LLM-assisted feature generation - with judgment about when LLMs add value vs. when classical methods do * Strong causal inference and experimental design background - matched and synthetic controls, difference-in-differences, propensity score matching, instrumental variables * Experience building recommendation, next-best-action, or audience scoring systems at scale using behavioral and third-party data * Able to communicate statistical methodology and model behavior clearly to non-technical audiences, including commercial and medical affairs stakeholders * Healthcare, life sciences, pharma analytics, or digital health experience strongly preferred; experience with real-world claims or HCP data, or scaling capabilities across multiple markets, is a plus ## Description * Lift measurement framework producing sponsor-facing outputs that support premium contract conversations * Decisioning and recommendation models live in production and personalizing the HCP experience at scale * Audience scoring infrastructure refreshing on cadence and integrated into commercial targeting workflows * LLM and generative AI capabilities integrated across the data science workflow, not siloed * ML platform infrastructure operational - experiment tracking, model registry, A/B testing, and production monitoring * Roadmap maintained and ready to extend into new specialty markets RESPONSIBILITIES * Shape the data science roadmap: Identify measurement, audience, and AI capabilities that create value in each specialty market, and build a function that scales with the business. * Build causal lift measurement: Own the framework that demonstrates how HCP engagement drives real-world prescribing change - matched and synthetic controls, lookalike populations, methodologies defensible to pharmaceutical medical affairs and legal, and repeatable across therapeutic areas. * Build decisioning and personalization systems: Develop next-best-action, recommendation, and audience intelligence models that personalize the HCP experience and identify high-value audiences for sponsor targeting at scale. * Apply LLMs and generative AI across the workflow: Use them for structured extraction, feature engineering, insight generation, and HCP profile enrichment - wherever they cut time-to-insight without compromising rigor. * Translate findings into commercial products: Turn model outputs into sponsor-facing measurement reports, audience intelligence packages, and ROI dashboards, and present methodology directly to pharmaceutical medical affairs and commercial teams. * Own the ML platform layer: Feature engineering, experiment tracking, model registry, A/B and holdout frameworks, and production monitoring on the company's cloud and data warehouse stack. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) - [Making Data Warehouses fast. A developer's story.](https://www.wearedevelopers.com/videos/302-making-data-warehouses-fast-a-developer-s-story) - [Hacking AI at the Edge of the Indian Ocean](https://www.wearedevelopers.com/videos/100177-hacking-ai-at-the-edge-of-the-indian-ocean) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [The Biggest German Tech Companies](https://www.wearedevelopers.com/magazine/424-the-biggest-german-tech-companies) - [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)