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Tiger Analytics

Delivers Data and AI transformation

Senior Data Scientist - Pharma

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeRemote in USA$120k - $140kRemote

About the Job

Requirements

  • Six to eight years of experience in data science or applied machine learning, including hands-on production work in next-best-action, next-best-content, recommendation, or personalization.
  • Strong Databricks experience, including Spark or PySpark, Delta Lake, and MLflow; Feature Store or Unity Catalog experience is a plus.
  • Solid grounding in machine learning, deep learning using PyTorch or TensorFlow, and reinforcement learning such as bandits, Q-learning/DQN, or PPO.
  • Proficiency in Python and SQL.
  • Experience taking models from prototype to production using MLOps practices such as CI/CD, monitoring, and retraining.
  • Experience with experimentation, A/B testing, and measuring incrementality.
  • A Bachelor's or Master's degree in a quantitative field.

Responsibilities

  • Design and deploy next-best-action and next-best-content models that select the appropriate action, channel, content, and timing for each customer or healthcare professional.
  • Build machine learning, deep learning, and reinforcement learning solutions, including contextual bandits, sequential decision models, and policy-based methods.
  • Develop propensity, response, and uplift models for the decisioning layer.
  • Run offline policy evaluations and online experiments to measure incremental impact.
  • Own Databricks training pipelines, including PySpark feature engineering, MLflow tracking, Unity Catalog lineage, and automated evaluation gates before production.
  • Design feedback loops so outcomes feed back into retraining.
  • Apply generative AI and large language models where useful, including 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.

Desired Qualifications

  • A Master's or PhD is preferred.
  • Life sciences or pharmaceutical commercial analytics experience, including omnichannel, healthcare professional or patient engagement, field force, or patient journey data.
  • Familiarity with customer relationship management, customer data platforms, or marketing automation platforms.
  • Causal inference and uplift modeling experience.
  • Experience with regulated or compliance-constrained data, such as HIPAA.
  • Databricks certifications.

About the Company

Tiger Analytics

Delivers Data and AI transformation

Tiger Analytics helps large organizations plan and execute Data and AI–led transformations at scale. It works with clients to translate business needs into data and AI initiatives, using an approach that combines business value mapping, agile operating models, and a platforms-based architecture, backed by partnerships with major hyperscalers. The company designs and delivers end-to-end data and AI solutions—from strategy and data engineering to model development and deployment—so that AI can be applied to tough, real-world problems. Unlike firms that rely mainly on standard playbooks, Tiger Analytics builds custom approaches and accelerators to suit each client’s value chain and operating model. With a global team of 5000+ technologists and consultants, the goal is to enable measurable value and practical outcomes through data and AI programs that work at enterprise scale.

Company size
1,001-5,000
Company stage
Not listed
Total funding
Not listed
Headquarters
San Jose, CA
Founded
2010

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