Portfolio Analytics Lead

Genentech•Daly City, CA

71d•$148,100 - $275,000•Onsite

About The Position

We advance science so that we all have more time with the people we love. The Portfolio Analytics Lead in Genentech Research and Early Development (gRED) Early Clinical Development Informatics (ECDi) Data Intelligence (DI) team is a strategic thought partner to key stakeholders and an integral contributor to the company’s clinical operational planning efforts. The role contributes to an integrated Clinical Operations Plan (iCOP) which is used to guide end-to-end, cross-business unit, Clinical Operations planning and strategies at the disease area (DA) level. The role provides strategic operational insights with their capabilities in the following areas: forecasting, landscape analysis, advanced data analysis, and project management, to support Clinical Operations and management for effective data-driven decision making. This role participates and leads in global workgroups and initiatives to define cross-business unit best practice for processing, analyzing, generating actionable insights, and presenting data in innovative and consumable ways to address inquiries, as well as to support business planning and strategies.

Requirements

Bachelor’s degree in Data Science, Mathematics, Statistics, Computer Science, Life Sciences, Public Health, or a related field; Graduate-level degree preferred.
7+ years of experience with Bachelors; 5+ years of work experience with Masters; 3+ years of work experience with PhD, in the following areas: Patient Insights, Investigator Insights, Forecasting, Competitive Intelligence, Advanced Data Analytics, Information Visualization, and Data Science in Clinical Operations in the pharmaceutical/biotech industry.
Strong proven experience working with and engaging Clinical Operations stakeholders, and acting as a strategic thought partner to teams.
Experience of leading/working with SMEs from cross-business units to understand and diagnose business problems, as well as using data driven methods to analyze and solve business situations.
Experience with scripting and analytical programming preferred (e.g., Python, R, SQL, JavaScript, or other JavaScript-based libraries)
Knowledge of snowflake/cloud, architecture, and data modeling concepts preferred.
Experience with various forecasting methods and techniques strongly preferred.
Record of portfolio management experience and effectively leading/working in a matrix environment with team members using influence without authority. Able to multi-task and re-prioritize work on short notice, able to lean in and manage through change.
Persuasive written and verbal communication skills, easily communicating complex ideas. Strong interpersonal skills and a consultative mindset, with the ability to develop strong partnerships.

Responsibilities

Work with cross-business unit Clinical Operations DA level workgroups (e.g., iCOP team), Clinical Operations leaders, project/study teams, lifecycle teams to understand business needs and priorities, as well as immediate scope of work.
Deliver integrated insights and analytics, trade-off analyses, and risk assessment to enable optimization of patient recruitment strategies, country footprint, and clinical site selection at DA level in addition to for study teams and ECD Clinical Operations management.
Proactively partner with relevant stakeholders to assess the health of the portfolio and identify opportunities to expedite evidence generation and to accelerate the delivery of studies and product launches.
Utilizes state-of-art methodologies (including predictive modeling, ML/AI and scalable prototypes) and tools to analyze complex data (Real World Data and internal data) and interpret analysis of results to measure project/study performance and guide portfolio-level decisions efficiently.
Take the initiative in identifying, interpreting, and communicating the effects that trial design elements, country and site selection, competitor activities and new engagement tactics will have on clinical trial recruitment and retention forecasts.
Lead relevant data science and analytics projects, manage the implementation of the product development cycle, and ensure the success of the product.
Actively lead/participate in related cross-functional communities and collaborate with subject matter experts (SMEs) from cross-business units in global workstreams. Through analytics expertise and deep technical knowledge, contribute to the creation and implementation of globally aligned strategies and tools.
Identify potential opportunities for continuous improvement; engage managers and peer groups regularly for coaching, assistance, and advocacy.
Lead and coach junior team members.
Consult with IT service and data governance teams to clarify data needs. Lead internal and/or external team members to acquire, aggregate and curate data and information.