Job Description

Locations

• Boston

Salary

Skills Required

• model developmentintermediate
• Pythonintermediate
• pipelines for trainingintermediate
• RWDintermediate
• Bayesian computingintermediate
• AI-native software engineering practicesintermediate
• data governanceintermediate
• cloud-native ML architecturesintermediate

Required Qualifications

• You have a Master’s or PhD in Data Science, Computer Science, Statistics, Applied Mathematics, Bioinformatics, or a related field (degree in phd in data science)
• You have 6+ years of experience applying advanced statistical and ML techniques in biomedical, clinical, or digital health domains (experience, 6 years)
• You have proven expertise in model development, simulation studies, and decision-support frameworks (experience)
• You have strong hands-on experience with Python or R, and ML libraries such as scikit-learn, TensorFlow, PyTorch, or similar (experience)
• You have a track record of translating complex domain questions into robust statistical models or ML systems (experience)
• You have experience building pipelines for training, evaluating, and deploying ML solutions in production environments (experience)
• You have demonstrated expertise with RWD, Bayesian methods, decision theory, high-dimensional data, or causal inference (experience)
• You have attention to detail and quality work with an ability to manage and prioritize multiple projects simultaneously, including both long-term and short-term initiatives (experience)
• You have excellent collaboration skills, including statistical consulting skills, interpersonal skills to contribute effectively in cross-functional team settings, ability to influence others without authority, and ability to build strong collaborative relationships with scientific and non-scientific partners (experience)
• You have capacity for independent thinking and ability to make decisions based upon sound principles (experience)
• You exhibit excellent strategic agility including problem-solving and critical thinking skills, and agility that extends beyond technical domain (experience)
• You demonstrate respect for cultural differences when interacting with colleagues in the global workplace (experience)
• You possess excellent verbal and written communication skills, specifically in the areas of presentation and writing, with the ability to explain complex technical concepts in clear language (experience)
• You have a Master’s or PhD in Data Science, Computer Science, Statistics, Applied Mathematics, Bioinformatics, or a related field (degree in phd in data science)
• You have 6+ years of experience applying advanced statistical and ML techniques in biomedical, clinical, or digital health domains (experience, 6 years)
• You have proven expertise in model development, simulation studies, and decision-support frameworks (experience)
• You have strong hands-on experience with Python or R, and ML libraries such as scikit-learn, TensorFlow, PyTorch, or similar (experience)
• You have a track record of translating complex domain questions into robust statistical models or ML systems (experience)
• You have experience building pipelines for training, evaluating, and deploying ML solutions in production environments (experience)
• You have demonstrated expertise with RWD, Bayesian methods, decision theory, high-dimensional data, or causal inference (experience)
• You have attention to detail and quality work with an ability to manage and prioritize multiple projects simultaneously, including both long-term and short-term initiatives (experience)
• You have excellent collaboration skills, including statistical consulting skills, interpersonal skills to contribute effectively in cross-functional team settings, ability to influence others without authority, and ability to build strong collaborative relationships with scientific and non-scientific partners (experience)
• You have capacity for independent thinking and ability to make decisions based upon sound principles (experience)
• You exhibit excellent strategic agility including problem-solving and critical thinking skills, and agility that extends beyond technical domain (experience)
• You demonstrate respect for cultural differences when interacting with colleagues in the global workplace (experience)
• You possess excellent verbal and written communication skills, specifically in the areas of presentation and writing, with the ability to explain complex technical concepts in clear language (experience)

Preferred Qualifications

• Experience leading technical design or mentoring junior team members (experience)
• Experience applying Agile software development practices, ideally for a product embedding statistical algorithms and/or GenAI (experience)
• Experience prototyping and launching innovative data science or AI products (experience)
• Experience deploying ML models in compliant, regulated environments (experience)
• Experience developing evidence synthesis models or methods (e.g., network meta-analysis) and/or approaches to construct data-driven priors for drug development (experience)
• Experience with Bayesian computing or probabilistic programming languages (PPLs), including Stan, PyMC, brms, or others (experience)
• Experience with AI-native software engineering practices (experience)
• Familiarity with data governance, privacy, and regulatory frameworks relevant to ML in pharma (experience)
• Exposure to multiple stages of the pharma development life cycle (e.g., early development, assessment of external molecules for business development, commercialization) (experience)
• Familiarity with cloud-native ML architectures, ML Ops tools, or real-world data pipelines (experience)
• Strong publication record or external visibility in scientific communities (experience)
• Experience leading technical design or mentoring junior team members (experience)
• Experience applying Agile software development practices, ideally for a product embedding statistical algorithms and/or GenAI (experience)
• Experience prototyping and launching innovative data science or AI products (experience)
• Experience deploying ML models in compliant, regulated environments (experience)
• Experience developing evidence synthesis models or methods (e.g., network meta-analysis) and/or approaches to construct data-driven priors for drug development (experience)
• Experience with Bayesian computing or probabilistic programming languages (PPLs), including Stan, PyMC, brms, or others (experience)
• Experience with AI-native software engineering practices (experience)
• Familiarity with data governance, privacy, and regulatory frameworks relevant to ML in pharma (experience)
• Exposure to multiple stages of the pharma development life cycle (e.g., early development, assessment of external molecules for business development, commercialization) (experience)
• Familiarity with cloud-native ML architectures, ML Ops tools, or real-world data pipelines (experience)
• Strong publication record or external visibility in scientific communities (experience)

Benefits

• general: 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.
• general: 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.

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