Data Scientist

United States - Alameda : 1360-1380 South Loop Road

Abbott

Innovative medical devices and health care solutions for cardiovascular health, diabetes management, diagnostic testing, nutrition, chronic pain and more.

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Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 114,000 colleagues serve people in more than 160 countries.

     

JOB DESCRIPTION:

Working at Abbott

At Abbott, you can do work that matters, grow, and learn, care for yourself and family, be your true self and live a full life. You’ll also have access to:

  • Career development with an international company where you can grow the career you dream of.

  • Free medical coverage for employees* via the Health Investment Plan (HIP) PPO

  • An excellent retirement savings plan with high employer contribution

  • Tuition reimbursement, the Freedom 2 Save student debt program and FreeU education benefit - an affordable and convenient path to getting a bachelor’s degree.

  • A company recognized as a great place to work in dozens of countries around the world and named one of the most admired companies in the world by Fortune.

  • A company that is recognized as one of the best big companies to work for as well as a best place to work for diversity, working mothers, female executives, and scientists.

The Opportunity

As a Data Scientist, you will lead the analysis and interpretation of numerous data sources (interventional clinical trial datasets, observational human studies and real world evidence) from people with diabetes (PWDs). Results will inform feature sets for products to help PWDs better manage their diabetes.  

What You'll Work On

The ideal candidate will be one who can effectively analyze source data sets and translate those findings into actionable insights that can be understood by cross functional stakeholders.  More specifically, they will be expected to do the following:  develop standardized analysis methods and dashboards for certain common datasets as well as bespoke methods for unique datasets, define and test hypotheses for each dataset, generate summary documents of results with recommendations, and lead translation of these recommendations into real-life embodiments for testing.  The nature of this work is highly interdisciplinary, so the ideal candidate should value working with people from different professional backgrounds and be able to cultivate working cross-functional relationships.

              A strong working knowledge of the diabetes disease state (etiology, pathogenesis, progression and treatment) is highly preferred.  Such a knowledge will allow the incumbent to more effectively understand datasets, define hypotheses and draw actionable conclusions.

Responsibilities:

  • Perform hypothesis-driven analysis of PWD user data from various sources (glucose monitors, medication delivery devices, activity trackers).

  • Utilize findings from data analysis to formulate product features for next generation decision support tools.

  • Effectively present findings and your own conclusions/recommendations to stakeholders of various backgrounds.  Requires the ability to aggregate and simplify results into memorable “take home” messages.

  • Develop standardized analysis methods and visualization dashboards for certain commonly structured datasets as well as bespoke methods for unique datasets

  • Define study endpoints, hypotheses and data analysis methods for human clinical trials.

  • Participate in R&D initiatives to utilize time series data sets from multiple medical devices in the development of decision support algorithms for people with diabetes

  • Assist system engineers in system-level characterization/verification of complex systems. 

  • Communicate effectively with and participate on cross functional development teams with good negotiating skills to direct multi-disciplinary teams toward solutions.         

  • Responsible for utilizing and maintaining the effectiveness of the quality system.

  • Responsible for compliance with applicable Corporate and Divisional Policies and performing other duties as assigned by management.

Required Qualifications

  • Bachelor’s degree is Required.  Degrees in Computer Science, Data Analytics or similar discipline including Mathematics, Statistics, Physics, or Engineering is preferred

  • Advanced degree in Life or Physical Science, Bioengineering, Biomedical Engineering or closely related discipline is preferred

  • Minimum 4 years of Product development experience in Engineering or physical science.

  • Advanced Experience with programming scripts such as Python, Java, Scala, C++ in Linux/Unix, and R

  • Experience in applying data analysis techniques to a large set of data using big data systems such as Hadoop, Spark, MongoDB, or similar software

  • Advanced analytics knowledge and application in the field of

  • Statistics

  • Mathematical programming

  • Business acumen and experience with operational or strategic systems

  • Ability to work on many subjects concurrently.

Preferred Qualifications

  • Advanced degree (Master’s or Doctorate) is preferred.

  • Experience credit for advanced degrees beyond BS (2 years for Master’s; 4 years for Doctorate).

  • Understanding of the diabetes space from disease etiology and pathogenesis through on-market devices and therapeutics is desired.

  • Significant experience with advanced data analysis of clinical or real world evidence data in either a medical device, pharmaceutical, biotechnology, or academic setting.

  • Demonstrated ability to translate data analysis findings into actionable outputs for product (or drug) development (eg: requirements, specifications, etc)

  • Significant experience utilizing machine learning techniques for problem solving.

  • MATLAB and Python proficiency are highly desired.

  • Able to perform proficiently under up-to-date regulatory requirements.

Apply Now
 

* Participants who complete a short wellness assessment qualify for FREE coverage in our HIP PPO medical plan. Free coverage applies in the next calendar year.

Learn more about our health and wellness benefits, which provide the security to help you and your family live full lives:  www.abbottbenefits.com

Follow your career aspirations to Abbott for diverse opportunities with a company that can help you build your future and live your best life. Abbott is an Equal Opportunity Employer, committed to employee diversity.

Connect with us at www.abbott.com, on Facebook at www.facebook.com/Abbott and on Twitter @AbbottNews and @AbbottGlobal

     

The base pay for this position is

$83,600.00 – $167,200.00

In specific locations, the pay range may vary from the range posted.

     

JOB FAMILY:

Research and Discovery

     

DIVISION:

ADC Diabetes Care

        

LOCATION:

United States > Alameda : 1360-1380 South Loop Road

     

ADDITIONAL LOCATIONS:

     

WORK SHIFT:

Standard

     

TRAVEL:

Not specified

     

MEDICAL SURVEILLANCE:

Not Applicable

     

SIGNIFICANT WORK ACTIVITIES:

Continuous sitting for prolonged periods (more than 2 consecutive hours in an 8 hour day), Continuous standing for prolonged periods (more than 2 consecutive hours in an 8 hour day), Keyboard use (greater or equal to 50% of the workday)

     

Abbott is an Equal Opportunity Employer of Minorities/Women/Individuals with Disabilities/Protected Veterans.

     

EEO is the Law link - English: http://webstorage.abbott.com/common/External/EEO_English.pdf

     

EEO is the Law link - Espanol: http://webstorage.abbott.com/common/External/EEO_Spanish.pdf
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Category: Data Science Jobs

Tags: Big Data Computer Science Data analysis Data Analytics Engineering Hadoop Java Linux Machine Learning Mathematics Matlab MongoDB Pharma Physics Python R R&D Research Scala Security Spark Statistics Testing

Perks/benefits: Career development Flex hours Health care Wellness

Region: North America
Country: United States

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