We are seeking a hands-on, highly skilled
Senior Data Scientist to join our advanced analytics and AI team supporting some of our large enterprise clients. In this role, You'll build the decisioning engine behind next best action (NBA) and next best content (NBC) for commercial teams. The work covers modeling, offline evaluation, and production deployment on Databricks.
Key Responsibilities:- Design and deploy NBA/NBC models that choose the right action, channel, content, and timing for each customer or HCP
- Build ML, deep learning, and reinforcement learning solutions, including contextual bandits, sequential decision models, and policy-based methods
- Develop propensity, response, and uplift models that feed the decisioning layer
- Run offline policy evaluation and online experiments to measure incremental impact
- Own Databricks training pipelines: PySpark feature engineering, MLflow tracking, Unity Catalog lineage, and automated evaluation gates before models reach production
- Design feedback loops so outcomes flow back into retraining
- Apply GenAI/LLMs where useful, such as content tagging, insight summarization, and content personalization
- Partner with engineering, marketing technology, and business stakeholders, and explain results to non-technical audiences
- Mentor junior data scientists and set modeling standards
Requirements- 6 - 8 years in data science or applied ML, with hands-on NBA, NBC, recommendation, or personalization work in production
- Strong Databricks experience (Spark/PySpark, Delta Lake, MLflow; Feature Store or Unity Catalog a plus)
- Solid grounding in machine learning, deep learning (PyTorch or TensorFlow), and reinforcement learning (e.g., bandits, Q-learning/DQN, PPO)
- Proficiency in Python and SQL
- Experience taking models from prototype to production with MLOps practices (CI/CD, monitoring, retraining)
- Experience with experimentation, A/B testing, and measuring incrementality
- Bachelor's or Master's in a quantitative field (Master's or PhD preferred)
Preferred (Not Required)- Life sciences or pharma commercial analytics (omnichannel, HCP/patient engagement, field force, patient journey data)
- Familiarity with CRM, CDP, or marketing automation platforms
- Causal inference and uplift modeling
- Experience with regulated or compliance-constrained data (e.g., HIPAA)
- Databricks certifications
BenefitsThis position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.
