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Bayer Linkedin · Posted 17d ago

CMC Statistician

Berkeley, California, United States

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Indexed description

At Bayer we’re visionaries, driven to solve the world’s toughest challenges and striving for a world where 'Health for all Hunger for none’ is no longer a dream, but a real possibility. We’re doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining ‘impossible’. There are so many reasons to join us. If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there’s only one choice.

CMC Statistician

CMC Statistician for Berkeley, CA to perform advanced statistical analyses & data mining; develop & test experimental designs, sampling techniques, and analytical methods; query large sets of structured & unstructured biological and biotechnology data from disparate sources; clean & validate data to ensure accuracy, completeness and uniformity for statistical analysis; develop mathematical & statistical models to simulate biologic processes, functions & behaviors, and report results; design experiments for biologics & perform data analysis using statistical methods and machine learning tools. Requires Ph.D. in Statistics, Applied Mathematics or closely related quantitative field & 1 yr experience in using Python and R to design, develop & deliver statistical models and machine learning algorithms using biotech data sets; monitoring biological systems & making recommendations regarding process control and optimization; using gitlab & Jupyter to transform semi-structured and unstructured biological process sensor data and biological product analytical data into features for model development; supporting biological processes, product development & GMP cell therapy manufacturing applying design of experiments & advanced statistical data analysis; querying biological process data & performing data mining and visualization in GCP, AWS and/or Domino; and developing models with genomic data to conduct time series & ANOVA analysis for biological data sets. Will also accept a Master’s degree in stated fields and 3 yrs stated experience. Telecommuting permitted from home office location within reasonable commuting distance of Berkeley, CA up to 3 days per week. Salary Range: Employees can expect to be paid a salary between $165,000.00 to $185,000.00. Additional compensation may include a bonus or commission (if relevant). Additional benefits include health care, vision, dental, retirement, PTO, sick leave, etc. The offered salary may vary within this range based on an applicant’s location, market data/ranges, an applicant’s skills and prior relevant experience, certain degrees and certifications, and other relevant factors. Mail resume to Jill Martin, Bayer HealthCare LLC, 800 N. Lindbergh Blvd., E2NE, St. Louis, MO 63167 or email resume to [email protected] . Include reference code below with resume.

YOUR APPLICATION

Bayer offers a wide variety of competitive compensation and benefits programs. If you meet the requirements of this unique opportunity, and want to impact our mission Health for all, Hunger for none, we encourage you to apply now. Be part of something bigger. Be you. Be Bayer.

To all recruitment agencies: Bayer does not accept unsolicited third party resumes.

Bayer is an Equal Opportunity Employer/Disabled/Veterans

Bayer is committed to providing access and reasonable accommodations in its application process for individuals with disabilities and encourages applicants with disabilities to request any needed accommodation(s) using the contact information below.

Equal Opportunity Employer Statement: Notice for U.S. Visitors: All information on this site is subject to compliance with local rule and regulations as they may vary from time to time and across different geographies, including, without limitation, U.S. Executive Orders.

Bayer is an E-Verify Employer.

Location: United States : California : Berkeley

Division: Enabling Functions

Reference Code: 878204

Contact Us

Email: [email protected]

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