Senior Data Scientist – Pharma

Job not on LinkedIn

🕒 October 22

🏄 California – Remote

🏄 California – Remote

💵 $120k - $140k / year

⏰ Full Time

🟠 Senior

📊 Data Scientist

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 1%

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Tiger Analytics

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2011

🏥 Healthcare

📦 Logistics

📣 Marketing

Healthcare • Logistics • Marketing

Tiger Analytics is a leading AI and analytics consulting firm that specializes in leveraging data science and machine learning to provide strategic business insights across various industries. They offer services in data strategy, AI engineering, and business intelligence to enable data-driven decision-making and digital transformation for their clients. Tiger Analytics collaborates with top technology partners like Microsoft, Google Cloud, and AWS to deliver cutting-edge solutions. They serve a diverse range of sectors including consumer packaged goods, healthcare, and finance, helping businesses operationalize insights and differentiate with AI and machine learning technologies.

📋 Description

• Design and deploy NBA/NBC models selecting 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 feeding the decisioning layer • Run offline policy evaluation and online experiments to measure incremental impact • Own Databricks training pipelines, including PySpark feature engineering, MLflow tracking, Unity Catalog lineage, and automated evaluation gates • Design feedback loops so outcomes flow back into retraining • Apply GenAI/LLMs for content tagging, insight summarization, and content personalization • Partner with engineering, marketing technology, and business stakeholders • 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) • Life sciences or pharma commercial analytics (preferred, not required) • Familiarity with CRM, CDP, or marketing automation platforms (preferred, not required) • Causal inference and uplift modeling (preferred, not required) • Experience with regulated or compliance-constrained data such as HIPAA (preferred, not required) • Databricks certifications (preferred, not required)

🏖️ Benefits

• Medical, Dental, Vision • Retirement Accounts • Long and Short Term Disability • Life Insurance • HSA/FSA Accounts (USA) • Discretionary time-off • Significant career development • Continuous learning and AI upskilling • Hands-on exposure to emerging technologies • Opportunities to build expertise in Generative AI, agentic AI, and next-generation data platforms • Equal employment opportunities

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