Principal Data Scientist

F. Hoffmann-La Roche AG; South San Francisco (CA); Hybrid; USD 217.000 - 404.000; Vollzeit

Zusammenfassung

Genentech, a member of the Roche group, seeks a Principal Data Scientist to lead Causal AI and Experimentation within Data Science and ML. You will design, develop, and industrialize enterprise-grade models to measure impact, optimize resources, and guide data-driven decisions.

You will mentor peers and set standards across cross-functional teams. You will work in a high-impact role bridging advanced causal methods with business strategy, embracing responsible AI and cutting-edge Bayesian and

Qualifikationen

• Bachelor’s Degree and 8+ years in Data Science, Statistics, or ML engineering.
• 5+ years in Causal Inference, Experimental Design, Measurement, and Optimization.
• Expert-level knowledge of open‑source ML frameworks (PyTorch, TensorFlow, scikit-learn, statsmodels, CausalML, DoWhy, EconML).
• Proficiency in Python and/or R; strong SQL.
• Deep familiarity with measurement packages (Robyn, LightweightMMM, Meridian).
• Experience scaling algorithms in big data environments (Spark, Databricks, Hadoop) and cloud platforms (AWS, GCP, or Azure).
• Excellent communication and ability to influence partners; rigorous experimental design.

Aufgaben

• Design and lead Causal AI, measurement, and experimentation projects.
• Build production-grade causal inference models (A/B testing, MMM, uplift).
• Scale algorithms to quantify causal impact and drive optimization.
• Collaborate with product, data engineers, ML engineers, and stakeholders.
• Mentor team members and set modeling standards.
• Translate causal concepts into actionable guidance for business leaders.
• Stay current with academic and industry advances in causal methods.

Kenntnisse

Causal Inference

Experimental Design

Python

R

SQL

Machine Learning

Big data

Cloud platforms

Communication

Mentoring

Ausbildung

MS or PhD in Statistics/Math/Data Science/CS

Tools

PyTorch

TensorFlow

scikit-learn

DoWhy

EconML

CausalML

Robyn

LightweightMMM

Meridian

Spark

Jobbeschreibung

The Opportunity

As a Principal Data Scientist - Causal AI & Experimentation (within our Data Science and Machine Learning team), you will serve as a technical leader and key domain authority for advanced experimentation, measurement, and optimization solutions across the CMG organization. In this high-impact, individual-contributor role, you will bridge the gap between cutting-edge causal methodology and high-stakes business strategy. You will drive the design, development, and industrialization of enterprise-grade causal AI and statistical models that measure business impact, optimize resource allocation, and guide data-driven decision-making. Working alongside other data scientists and engineers, you will help shape the technical strategy for measurement and experimentation initiatives. You will serve as a mentor to senior and junior data scientists, establish best-in-class modeling standards, and partner closely with cross-functional teams to deliver scalable AI solutions.

Key Responsibilities

• Drive the technical design and methodology for key Causal AI, measurement, and experimentation projects, translating complex business objectives into robust mathematical and algorithmic frameworks.
• Design, build, and deploy production-grade statistical, econometric, machine learning, and causal inference models (e.g., A/B & quasi-experimentation, Media/Marketing Mix Modeling, synthetic controls, uplift modeling, and non‑parametric measurement).
• Develop scalable algorithms to quantify the true causal impact of promotional and non‑promotional activities, generating actionable recommendations for business optimization.
• Partner closely with business and technical product managers, data engineers, ML engineers, MLOps, and commercial stakeholders to translate business priorities into scalable technical requirements and drive the end‑to‑end industrialization of Causal AI applications.
• Act as a technical authority and subject matter expert (SME) in Causal AI. Provide technical guidance, perform code and design reviews, and mentor team members to foster technical excellence and continuous learning.
• Translate complex causal modeling and statistical concepts into clear, compelling narratives and actionable guidance for both technical teams and non‑technical business leaders.
• Stay at the forefront of academic and industry advancements in Causal AI, Causal ML, Bayesian modeling, and Generative AI, advocating for responsible AI practices and bringing novel approaches into our measurement ecosystem.

Who You Are

You have aA Bachelor’s Degree and 8+ years of work experience, or an equivalent mix of education and work experience, is required. You have 8+ years of relevant industry experience in Data Science, Applied Statistics, or ML engineering with a proven track record of architecting and shipping impactful data science products. 5+ years of hands‑on specialization in Causal Inference, Experimental Design, Measurement, and Optimization (e.g., A/B testing, quasi-experiments, observational causality, Market Mix Modeling, Bayesian modeling, uplift modeling) Expert‑level knowledge of open‑source frameworks for ML, statistics, and causal inference (e.g., PyTorch, TensorFlow, scikit‑learn, statsmodels, CausalML, DoWhy, EconML). Advanced proficiency in Python and/or R, along with strong SQL skills for complex database management and data manipulation Deep familiarity with open‑source measurement packages (e.g., Robyn, LightweightMMM, Meridian). Hands‑on experience scaling algorithms using big data environments (Spark, Databricks, Hadoop) and cloud platforms (AWS, GCP, or Azure). Exceptional verbal and written communication skills with a demonstrated ability to influence key partners, align business priorities, and explain complex mathematical methodologies to business leaders. Strong critical thinking abilities with rigorous attention to detail regarding experimental design, bias mitigation, and causal validity.

Preferred Qualifications

• Advanced degree (MS or PhD preferred) in Statistics, Mathematics, Applied Economics, Computer Science, Data Science, or a related quantitative field with a focus on AI/ML or Causal Inference with 6+ years of relevant industry experience in Data Science, Applied Statistics, or ML engineering
• 6+ years with a PhD
• Experience working with complex, large‑scale dataset structures in healthcare, pharmaceuticals, or highly regulated environments (including longitudinal patient‑level data, syndicated sales, or promotional data).
• Familiarity or hands‑on experience integrating Deep Learning or Generative AI techniques with Causal AI frameworks.
• A history of contributions to open‑source data science tools or peer‑reviewed publications in causal inference, experimentation, or measurement technology.

Location

This role is based in South San Francisco and offers a hybrid schedule working 3 day per week on campus. Relocation benefits are NOT offered on this posting. The expected salary range for this position based on the primary location of South San Francisco, CA is $217,400/yr to $403,700/yr. Actual pay will be determined based on experience, qualifications, geographic location, and other job‑related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.

Benefits

Benefits #LI-CM4 Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company’s policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws. If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.

Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company’s policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws. If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.

Who We Are

Genentech, a member of the Roche group and founder of the biotechnology industry, is dedicated to pursuing groundbreaking science to discover and develop medicines for people with serious and life‑tensive diseases. To solve the world's most complex health challenges, we ask bigger questions that challenge our industry and the boundaries of science to transform society. Our transformational discoveries include the first targeted antibody for cancer and the first medicine for primary progressive multiple sclerosis. The next step is yours.

Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company’s policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws. If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.