Senior Data Scientist

About the role

In this role, you will design and implement statistical models to address large-scale health data challenges, working closely with cross-functional teams to define project goals and success metrics. Your contributions will directly impact the efficiency of life sciences companies in delivering therapies to patients.

Veeva Systems is a mission-driven organization that emphasizes values like customer success and employee well-being. As a remote-first company, you will have the flexibility to work from home or in the office, enabling you to thrive in your preferred environment while contributing to meaningful projects.

The salary range for this position is between $115,000 and $195,500, reflecting the seniority and expertise required.

Skills that matter here

• Python: Proficiency in Python is essential for developing data science solutions.
• ML libraries: Experience with machine learning libraries is important for implementing statistical models.
• NLP tools: Knowledge of NLP tools will aid in developing AI solutions for health data.
• Big data processing: Skills in big data processing are necessary for handling large healthcare datasets.
• analytics capabilities: Strong analytics capabilities are required to monitor model performance and ensure data quality.

Who this role suits

• A data scientist with a strong foundation in statistics and machine learning.
• Someone comfortable with greenfield projects and minimal supervision.
• An individual who collaborates well with cross-functional teams.
• A proactive problem solver who enjoys experimenting with new techniques.

From the employer

What you'll do

• Design and implement statistical models and data science solutions to tackle large-scale health data challenges.
• Collaborate with cross-functional teams (Product, Data Analytics, Engineering) to define problem statements, success metrics, and deliverables.
• Develop and validate inference-based models, NLP/AI solutions, and scalable data processing pipelines.
• Experiment with novel techniques to address identity resolution, data merging, and data quality issues while preserving privacy.
• Monitor model performance, conduct quality assurance, and iterate based on feedback and measurement results.

Who you are

• Strong background in statistics, machine learning, and data science with experience applying these skills to large healthcare-related datasets.
• Proficient in Python (or similar) and modern data science toolkits; experience with NLP, ML, AI on big data is a plus.
• Ability to work with stakeholders across Product, Analytics, and Engineering to translate business problems into modeling solutions.
• Comfort with greenfield projects, experimentation, and working with minimal supervision.