Senior Knowledge Analyst, Data Science - Life Sciences

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.

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.

• 3+ 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 deliverables