Data Management TA Lead, Early Development at Genentech

Daly City, California, United States -

Full Time

Start Date

Immediate

Expiry Date

17 Jun, 26

Salary

306500.0

Posted On

19 Mar, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Management Strategy, Clinical Development, Team Leadership, Data Quality, Data Integrity, Data Readiness, Biostatistics, Data Science, Clinical Operations, Technical Leadership, Process Optimization, Talent Development, Mentoring, CDISC Standards, Clinical Data Systems, Performance Management

Industry

Biotechnology Research

Description

The Position A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Roche. This role is in Early Development Biometrics (EDB), a core function within Product Development Data Sciences (PDD) that provides strategic leadership and scientific rigor across early clinical development at Roche. We partner across Biostatistics, Analytical Data Science, and Data Management to enable data-driven decision-making from first-in-human through proof-of-concept studies. As trusted partners in early development, we design efficient and innovative clinical trials, apply rigorous statistical methods, and implement high-quality programming and analytical solutions to accelerate timelines, de-risk development, and increase the probability of technical success. Our integrated teams operate with agility and scientific depth, supporting exploratory analyses, early regulatory engagements, and complex data-generation needs across therapeutic areas. Together, we bring scientific rigor, technical innovation, and strategic insight to shape the future of early development and deliver better outcomes for patients. Early Development Biometrics is also home to Methods Collaboration & Outreach (MCO), which enables the most impactful use of quantitative methodology across PDD through internal consultation, external collaboration, and continuous capability building; and Visual Analytics, which creates and maintains interactive dashboards that drive high-quality Medical Data Review (MDR) and safety signal detection, aligned with Risk-Based Quality Management (RBQM) principles and Critical-to-Quality (CtQ) endpoints. The Opportunity: The Data Management TA Lead in Early Development Biometrics is accountable for setting and executing the data management strategy across a therapeutic area (TA), ensuring high-quality, reliable, and analysis-ready data in support of early-phase clinical development. This role directly leads a team of Data Managers responsible for ensuring data quality, integrity, and readiness across multiple studies, partnering closely with Biostatistics, Data Science, Clinical Operations, and vendor teams. It provides technical leadership across multiple programs, enabling consistent, scalable, and scientifically aligned data practices tailored to the unique demands of early research. As a key leader within the Early Development Biometrics function, the TA Lead anticipates and navigates complexities such as evolving endpoints, exploratory data types, and limited standardization, driving fit-for-purpose solutions that support decision-making under uncertainty. This includes aligning data strategies with early clinical development goals and ensuring biometrics deliverables are both scientifically rigorous and operationally feasible. With deep subject matter expertise and a strong understanding of the data lifecycle, the TA Lead also contributes to process optimization, standards evolution, and innovation across early development programs. This role also drives continuous improvement, talent development, and a culture of accountability, collaboration, and innovation within the data management team. You will lead a diverse team of 6-8 data managers, and will also have overall responsibility for a early development program area. Your primary responsibilities will be in service to your direct reports, and to the molecule or disease area team you are supporting. You will help match talent to opportunities by understanding the skills and aspirations of your team and understanding the PDD strategic context and possible opportunities. You will coach and mentor through your extensive data management experience and drug development expertise. Additionally, you will establish and foster key internal and external relationships, purposefully collaborating to be at the forefront of our industry. You provide strategic leadership for data management across a therapeutic area in early development, ensuring data strategies align with scientific objectives and evolving program needs You design and drive implementation of fit-for-purpose data practices that support flexible study designs, exploratory endpoints, and rapid iteration You anticipate and solve complex challenges involving non-standard data, external data sources, and limited precedent, ensuring readiness for internal and downstream decision-making You lead alignment across biometrics contributors (e.g., data standards, statistical programming) to ensure consistency, efficiency, and data reusability across early-phase programs You represent Early Development Data Management in internal forums focused on functional excellence, capability development, and process innovation You set quality expectations and provide expert guidance across studies, serving as a senior advisor and mentor to study-level data managers and other data contributors You lead and develop a team of Data Managers supporting multiple studies across one or more molecules within a subset of a disease area You set clear goals, development plans, and performance expectations to enable functional growth and delivery You manage team workload, capacity planning, and study allocation based on program complexity and milestones You foster collaboration and information sharing across study teams and with cross-functional partners You represent data management in molecule-level or DA-level forums and ensure alignment with clinical and data science strategies You role-model effective leadership behaviors and coach team members to grow technical, leadership, and strategic skills You serve as a role model in demonstrating Roche’s Leadership Commitments and the Pharma Operating Principles You work with other DM TA Leads and People Leaders within Early Development Biometrics, Data Management, and across PDD to support continued development of the PDD talent pipeline through work on PDD products and via ongoing training, mentoring, and coaching Who You Are: You hold a Bachelor’s or Master’s degree in life sciences, informatics, statistics, computer science, or a related field You bring 12+ years of experience in clinical data management, with a focus on complex or novel data types in early-phase development You are recognized as an expert in data strategy, standards, and quality frameworks for early-stage clinical trials You have a deep understanding of data flow, collection, and transformation processes across the R&D ecosystem You demonstrate the ability to anticipate technical data challenges and design scalable solutions under conditions of scientific uncertainty You are skilled in TA-level data planning, study startup consultation, and enabling evidence readiness across multiple programs You have excellent written and verbal communication skills, with the ability to clearly articulate technical concepts and implications to internal audiences You possess strong expertise in CDISC standards, regulatory requirements, and clinical data systems (e.g., EDC, eCOA, lab systems) You have experience mentoring and developing team members, with strong performance management skills You can operate independently, make strategic trade-offs, and manage cross-study resource planning You demonstrate respect for cultural differences when interacting with colleagues in the global workplace Preferred Qualifications: Expertise in early development data strategies, including handling of exploratory endpoints, biomarker data, and adaptive trial designs Experience supporting early-phase regulatory submissions (e.g., IND, CTA) and preparing data for downstream readiness Demonstrated leadership in evolving data management practices (e.g., modular CRFs, flexible standards, decentralized data sources) Proven ability to mentor or advise study-level data managers, raising overall quality and consistency across a TA Awareness of emerging industry practices (e.g., automation, FAIR data, AI-assisted QC) and ability to translate them into fit-for-purpose functional improvements Relocation benefits are not available for this posting The expected salary range for this position based on the primary location of California is $165,100-$306,500. 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 #PDDT #PDDSSF 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.

Responsibilities

The Data Management TA Lead is accountable for setting and executing the data management strategy across a therapeutic area, leading a team of Data Managers to ensure high-quality, reliable, and analysis-ready data for early-phase clinical development. This role involves providing strategic leadership, coaching team members, managing workload, and ensuring data strategies align with scientific objectives and evolving program needs.