Senior Data Analyst

Job Description

At Gilead, we’re creating a healthier world for all people. For more than 35 years, we’ve tackled diseases such as HIV, viral hepatitis, COVID-19 and cancer – working relentlessly to develop therapies that help improve lives and to ensure access to these therapies across the globe. We continue to fight against the world’s biggest health challenges, and our mission requires collaboration, determination and a relentless drive to make a difference.

 

We empower our leaders to step up, share ideas, listen, learn, and lead. We’re welcoming bright, diverse, and imaginative minds; we’re nurturing them to foster an environment of inclusion and growth where innovation is encouraged. We expect our people leaders to model that environment, and to focus on creating inclusion, developing talent, and enabling teams.

 

Every member of Gilead’s team plays a critical role in the discovery and development of life-changing scientific innovations. Our employees are our greatest asset as we work to achieve our bold ambitions, and we’re looking for the next wave of passionate and ambitious people ready to make a direct impact. Join Gilead and help create possible, together.

Job Description

Kite is seeking a highly motivated individual with data science experience to work on statistical analysis and modeling to support for the manufacturing of innovative T cell therapies used for cancer treatment. 

As a Senior Data Analyst for Manufacturing Sciences and Technology (MSAT), you will develop, evaluate, and deploy models to support decision making within MSAT. Deliver this by driving commercial GMP manufacturing statistical techniques, predictive and trending analysis that would provide oversight for GMP manufacturing for Kite’s engineered autologous T cell therapy products. 

Act as an internal consultant by integrating with different departments to identify opportunities, scope and define problems, performing data analysis, and interpret the results, draw conclusions, and present findings / recommendations to appropriate groups to help identify actionable steps to be taken by cross-functional and leadership teams. Mentor more junior staff, guide predictive model development across team, define how to use the models and train users on integration.

In your new role, you will:

• Undertake preprocessing of structured and unstructured data;

• Collect, cleanse, and understand complex data sources to enable proper analytical modeling;

• Build actionable KPIs, quality dashboards, informative deep dives, and scalable data products;

• Research, design, develop, test, and implement advanced analytics methods to drive insights;

• Analyze data to discover trends and patterns;

• Define and develop programming for decision support solutions that leverage predictive, prescriptive, and scenario optimization tactics;

• Build advanced process monitoring analytics based on multivariate analysis and inform improvements within MSAT;

• Conduct proper stakeholder management to ensure alignment;

• Design and build advanced visualization tools that will simplify the outputs of the models, with the goal of being integrated into a self-service operational model across MSAT;

• Develop professional presentations and project status reporting

• Additional duties as assigned.

Your profile

• You have an undergraduate Degree in Computer Science, Engineering, Mathematics, Statistics or a similar field. Master's degree preferred;

• You have previous work experience in biotechnology and pharma industry with data analytics, applied statistics, quantitative modelling and statistical analysis using R,JMP or Statistica. Familiarity with predicting modeling is a plus;

• You have previous experience or willing to learn programming languages such as R and SQL to develop and apply advanced modeling;

• Experience with data visualization tool Power BI or Spotfire;

• Well versed in cGMP manufacturing and regulatory regulations and requirements for pharmaceuticals and devices;

• Demonstrated ability to translate analytical insights into clear recommendations and effectively communicate them to technical and non-technical stakeholders;

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