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Senior Knowledge Analyst, Data Science - Life Sciences
Job ID: 88879
Who You'll Work With
You will join a diverse team of data scientists, engineers, product managers and translators as part of the Life Sciences Data Center of Excellence (CoE), within the McKinsey Life Sciences Practice. McKinsey's Life Sciences practice serves clients across multiple functional service lines spanning Commercial, R&D, and Operations. You'll be responsible for creating next-generation data and analytic solutions that help us serve clients and stay on the cutting edge in the industry. The Data CoE is a highly visible team and a high-profile position; the Data CoE works regularly with McKinsey life sciences senior leaders and clients.
What You'll Do
You will be responsible for creating next-generation data and analytic solutions that help serve clients and stay on the cutting edge in the industry.You will be analyzing large amounts of medical and pharmacy claims data to drive insights that will be used to make strategic decisions for clients. You will partner with client teams across project settings to drive and produce analyses and enable quick-turn analytics client development work. You will develop solutions and products to craft reusable data-driven insights. You will serve as an advocate for the use of data and analytics, guiding teams on the proper selection of datasets and analytic strategies to ensure an increase in the value of impact delivered to clients. You will collaborate across other practices, analytics groups, and technical teams to ensure efforts are synergistic and cutting-edge. You will also maintain and deliver a compelling portrayal of McKinsey's data ecosystem and capabilities to clients and internal stakeholders; drive awareness of the firm's policies related to data risk and refine/operationalize KPIs.
Qualifications3+ years of professional experience as a data analyst or data scientist
Bachelor's or advanced professional degree in engineering, computer science, physical sciences, statistics, data science or medicine from a recognized accredited institution of higher learning, college, or university
Working with, processing, and analyzing healthcare medical and pharmacy claims data, EMR data, clinical trials data, commercial data, and other types of data relevant for healthcare, pharmaceutical and medical device business use cases
Working knowledge of at least two claims data sets (e.g. IQVIA, Symphony, Healthverity, CMS, DRG, Compile, Komodo, Truven, etc.)
Applying data science methods (i.e., statistical modeling, machine learning techniques: regression, forecasting / predictive modeling, decision trees) to healthcare and Life Sciences business problems
Understanding key terminologies including: ICD-10, NDC, CPT, HCPCS, NPI, SNOMED, LOINC, RxNorm
Proficiency in at least two of the following coding languages: SQL, Python, or R
Proficiency in at least one of the following visualization/BI tools: Tableau, PowerBI, Qlik, or similar visualization/BI tools
Proficiency in handling large amounts of data in at least one of the following cloud computing tools: Snowflake, Microsoft Azure cloud, or AWS
Developing and executing detailed analytics workplan and presenting to senior stakeholders and clients
Communicating analytical and technical concepts to both technical and non-technical colleagues
Consulting experience within Life Sciences, Pharmaceutical, Healthcare, biotech or MedTech device industries, creating and contributing to presentations and client deliverablesApply Now
Apply LaterFOR U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employmen without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by applicable law.
Certain US jurisdictions require McKinsey & Company to include a reasonable estimate of the salary or hourly range for this role.
For new joiners for this role in the United States, including all office locations where the job may be performed, a reasonable estimated range
is $125,000 - $130,000 -to help you understand what you can expect. This reflects our best estimate of the lowest to highest
[salary/hourly wages] for this role at the time of this posting, ensuring you have a clear picture right from the start, though it's important
to remember that actual salaries may vary. Factors like your office location, your unique blend of experience and skills, start date and our current
organizational needs all play a part in determining the final figure. Certain roles are also eligible for bonuses, subject to McKinsey's discretion
and based on factors such as individual and/or organizational performance.
Additionally, we provide a comprehensive benefits package that reflects our commitment to the wellness of our colleagues and their families.
This includes medical, mental health, dental and vision coverage, telemedicine services, life, accident and disability insurance, parental leave and family planning benefits, caregiving resources, a generous retirement contributions program, financial guidance,
and paid time off.
FOR NON-U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity employer. For additional details
regarding our global EEO policy and diversity initiatives, please visit our
McKinsey Careers and
Diversity & Inclusion sites.
Job Skill Group - CSS Pre-Associate
Job Skill Code - SFDS - Senior Fellow, Data Science
Function - Technology
Industry - Life Sciences
Post to LinkedIn - Yes
Posted to LinkedIn Date - Tue Aug 15 00:00:00 GMT 2023
LinkedIn Posting City - New York
LinkedIn Posting State/Province - New York
LinkedIn Posting Country - United States
LinkedIn Job Title - Senior Knowledge Analyst, Data Science - Life Sciences
LinkedIn Function - Analyst;Consulting
LinkedIn Industry - Biotechnology;Health, Wellness and Fitness
LinkedIn Seniority Level - AssociateEqual Opportunity Employment DisclaimerMcKinsey & Company is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, national origin, disability, veteran status, and other protected characteristics.