Senior Data Scientist - Measurement & Optimization

The Commercial Data Science (CDS) team is committed to delivering production level work and building machine learning systems with an enterprise approach. CDS is involved in Genentech’s digital transformation to build an Integrated Customer Experience (ICX) which uses a large range of data sources (both structured and unstructured) and AI/ML algorithms to find patterns and deliver an automated experience to the end user.

The Opportunity

The Senior Data Scientist will bring their expertise in Statistical Modeling and Machine Learning for Measurement and Optimization. The ideal candidate has significant hands-on experience developing predictive models and communicating technical findings/insights to non-technical business teams for effective pull-through. An excellent Senior Data Scientist in the CDS team has a strong bias for execution, is able to operate independently, and is a great communicator, collaborator, innovator, and visionary.

• The Senior Data Scientist will lead and guide Data Science and some Data Engineering elements of AI/ML projects.

• Drive the development, deployment and industrialization of enterprise applications using advanced Statistical, Econometric, and Non-parametric modeling techniques to quantify the impact of promotional and non-promotional activities and generate recommendations for improvement.

• You will develop a deep understanding of customers and market dynamics, and apply your technical skills to advance that knowledge and guide the organization, delivering products that help create an integrated customer experience for customers.

• Help partners define clear, impactful business priorities, and where possible, use their own expertise or existing analysis/research to influence and guide. 

• Apply Machine Learning and Statistics based approaches to answer a variety of complex business questions using multiple data sources and technical tools.

• Act as subject matter expert for applicable Data Science and other advanced analytical methodologies, programs, and projects, particularly in the areas of Statistical Modeling, A/B testing, Experimental Design, and Time-Series analysis.

• Collaborate within cross-functional teams to develop efficient machine learning based applications, gain alignment and deliver impactful business insights; engage necessary partners to enable better decision-making.

• Openly share perspectives and insights to elevate team thinking and drive a balanced, integrated point of view; effectively weigh and communicate trade-off considerations.

• Take an enterprise attitude, linking individual responsibilities with broader organization; focus on outcomes that provide most business value.

• Demonstrate a bias for execution, self accountability, and results ownership.

• This position is based in SSF and relocation benefits are not available.

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Who You Are

• You have a BS, MS, or PhD in a relevant field: Data Science; Computer Science; Applied Mathematics, Statistics, Economics, Engineering or related field required; focus on Artificial Intelligence (AI) or Machine Learning (ML) preferred.

• 5 to 7+ years of relevant industry work experience required (transferable skills across multiple industries is a huge plus ).

• Experience (3+ years) in the application of Statistical Modeling techniques to enterprise data, with demonstrated ability to drive tangible results.

• Expertise in most of the following quantitative fields: Machine Learning, Deep learning, Applied Statistics, A/B Testing, Mathematical Optimization Techniques, Causal Inference, Bayesian Modeling, and Forecasting.

• Proficiency in using open source libraries and packages such as Pandas, Numpy, Sklearn, TensorFlow, Keras, PyTorch, statsmodels etc. to solve Enterprise problems.

• Working knowledge of recent advancements in Econometric and Time-Series modeling techniques and use of open-source libraries like Robyn, LightweightMMM, and Meridian.

• Solid foundational knowledge in Machine Learning with applications focused on Measurement, Causal Inference, and Experimentation.

• Experience working with large, complex data using Hadoop or Spark or any other big data platforms.

• Proficiency with industry-standard programming languages such as R or Python

• Experience with other Data Science and cloud-computing tools and platforms (AWS, GCP, etc.).

• Strong knowledge of secondary data sources including syndicated sales, promotional & marketing data, longitudinal patient level data.

The expected salary range for this position based on the primary location of CA is $172,500 - $320,300. 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

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Genentech is an equal opportunity employer, and we embrace the increasingly diverse world around us. Genentech prohibits unlawful discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin or ancestry, age, disability, marital status and veteran status.