Senior Data Scientist

Talentify; South San Francisco (CA); Hybrid; USD 180,000 - 230,000; Full time

Job summary

TalentBurst is seeking a Senior Data Scientist in South San Francisco, CA (hybrid) for a 6-month engagement. You will develop, deploy, and industrialize ML-driven applications, shaping business priorities and delivering actionable insights across Commercial and Medical domains.

You will collaborate with data science engineers and product owners, maintain data governance, and ensure compliance while staying at the forefront of AI innovations.

Qualifications

• Bachelor's degree in a quantitative field and 5+ years in data science or related roles.
• Strong programming skills in Python or R and solid SQL knowledge.
• Proven experience delivering end-to-end ML solutions in production environments.

Responsibilities

• Lead development, deployment, and industrialization of ML-powered enterprise applications.
• Collaborate with cross-functional teams to align data initiatives with business priorities.
• Ensure data quality, governance, and regulatory compliance across projects.
• Communicate complex findings clearly to non-technical stakeholders.

Skills

Python

R

SQL

Machine Learning

Deep Learning

MLOps

Cloud computing

Communication

Education

Bachelor's degree in Statistics, Mathematics, Computer Science

Tools

TensorFlow

PyTorch

AWS/GCP

Hadoop

Spark

Tableau/Qlik/Data Studio

Job description

Senior Data Scientist

South San Francisco, CA - hybrid

Duration: 06 Months

Visa Acceptable - USCs and GCs

The Opportunity

The Senior Data Scientist in Data, Analytics, and AI develops, deploys, and industrializes enterprise applications leveraging machine learning techniques to extract value from structured and unstructured data across Commercial and Medical domains. Acting as a strategic thought partner, the role involves shaping impactful business priorities, collaborating cross-functionally, and delivering actionable insights. The position requires a strong execution mindset, commitment to data quality and governance, and the ability to communicate complex findings to different audiences all while staying at the forefront of AI innovation and aligning with Genentech s standards and compliance.

Key Job Responsibilities

• Drive the development, deployment, and industrialization of enterprise applications using machine learning techniques (e.g., classification, regression, and forecasting) to generate value from structured and unstructured data for Commercial and Medical organizations.
• Help stakeholders define clear, impactful business priorities, and where possible, use their own expertise or existing analysis/research to influence and guide.
• Collaborate with data science product owners/managers, data leads, ML Engineers, and other teams to develop efficient machine learning-based applications, gain alignment, and deliver impactful business insights.
• Strong commitment to data ethics, model validation standards, and regulatory compliance.

Who You Are

• Bachelor's degree in Statistics, Mathematics, Computer Science, or a related quantitative field.
• Minimum 5 years of experience in data science or related roles.
• Proficiency in programming languages such as Python, R.
• Knowledge of SQL for database management.
• Strong expertise in Machine Learning and Deep Learning techniques
• Demonstrated experience developing the end-to-end ML solutions, from conceptualization and prototype development through to production deployment and monitoring.
• Experience with other Data Science and cloud‑computing tools and platforms (AWS, GCP, etc.).
• Excellent verbal and written communication skills, with the ability to present complex data analyses to non‑technical stakeholders.
• Proven track record of collaborating within cross‑functional teams, partnering directly with data science product owners, ML engineers, and MLOps teams to deploy efficient, production‑ready machine learning applications.
• Proven ability to translate ambiguous business challenges into clear, data‑driven analytical initiatives that align with organizational objectives.
• Strong understanding of MLOps best practices, including CI/CD pipelines, model versioning, and performance monitoring to ensure scalability and reliability in production environments.
• Strong critical thinking and problem‑solving abilities, with a detail‑oriented approach to data analysis.

Preferred Qualifications

• Experience applying advanced data science and predictive modeling techniques within the healthcare/pharmaceutical industry, with a demonstrated commitment to strict data governance, regulatory compliance, and high‑quality model validation standards
• Experience with deep learning frameworks (e.g., TensorFlow, PyTorch).
• Contributions to open source projects or publications in data science.
• Relevant certifications in data science, machine learning, or AI technologies (e.g., Certified Analytics Professional, AWS or similar certifications).
• Experience working with large, complex data using Hadoop or Spark or any other big data platforms.
• Proficiency using ML in a variety of contexts such as insight generation, ROI calculation, text classification, clustering etc.
• Experience with data visualization tools such as tableau, and/or Qlik, and/or data studio etc.
• Experience translating research or analysis to communicate (in presentations and in writing) concise and compelling business stories that influence decisions and strategy.
• Location
• This position is based in South San Francisco, CA at our client Campus
• Relocation benefits are NOT available for this posting

Why TalentBurst?

At TalentBurst, we deliver more than talent, we deliver outcomes. We partner with you to move quickly and connect you to opportunities aligned with your skills and long term growth.

Backed by precision, transparency, and results, we connect top talent with leading organizations through trusted partnerships.

We offer competitive compensation and comprehensive benefits, including medical, dental, vision, and retirement options.

TalentBurst is an equal opportunity employer committed to an inclusive and diverse workforce.