Sr Data Scientist

at  McKesson

Job Title: Sr. Data Scientist (1 year FTC)
Job Summary: Finance is of paramount importance to McKesson. You will be part of a talented team of data scientists and collaborate with financial analysts and cross-functional data and enablement teams to improve decision-making within both our corporate and business unit focused finance groups. If you’re innately curious about data, AI and finance and seek an opportunity to create an impact at large scale organization, this might be the perfect role for you.

Key Requirements:

• Requires 6+ years of hands-on work experience developing and applying advanced analytics solutions in a corporate

Critical skills:

• Hands-on experience and foundational knowledge to build robust AI/ML models.
• Proficient in many of the following techniques - time series, clustering, NLP, neural networks, KNN, decision trees, regression, etc.
• Demonstrated professional experience working on programming languages, tools, and platforms like Python, Databricks, Snowflake, etc.
• Ability to clearly communicate technical concepts and results to non-technical audiences.
• Familiarity with data privacy standards, methodologies, and best practices

Additional skills:

• Positive and flexible attitude to enable adjusting to different needs in an ever-changing environment.
• Teams up and collaborates for speed, agility, and delivery and operational excellence.
• Experience working with large healthcare datasets is a plus.
• Expertise in data visualization tools such as Power BI, Tableau and Looker is a plus

Education:

• MS or PhD in data science or related fiel

• Develop AI/ML models for Finance applications to enhance effectiveness and efficiency of financial decision, e.g., revenue and cash forecasting, customer segmentation, payment prediction models.
• Build data science solutions to support financial management and optimization.
• Collaborate with cross-functional teams to understand business requirements.
• Build technically sound, business-friendly presentations ranging across end-to-end project activities (e.g., proposal, proof-of-concept analysis, modeling results, progress tracking, read outs).
• Design and execute experiments to test hypotheses.
• Guide other data scientists on the team.
• Manage resources from third-party vendors as needed.
• Stay updated on advancements in AI/ML space broadly

Key Requirements:

• Requires 6+ years of hands-on work experience developing and applying advanced analytics solutions in a corporate.

Critical skills:

• Hands-on experience and foundational knowledge to build robust AI/ML models.
• Proficient in many of the following techniques - time series, clustering, NLP, neural networks, KNN, decision trees, regression, etc.
• Demonstrated professional experience working on programming languages, tools, and platforms like Python, Databricks, Snowflake, etc.
• Ability to clearly communicate technical concepts and results to non-technical audiences.
• Familiarity with data privacy standards, methodologies, and best practices.

Additional skills:

• Positive and flexible attitude to enable adjusting to different needs in an ever-changing environment.
• Teams up and collaborates for speed, agility, and delivery and operational excellence.
• Experience working with large healthcare datasets is a plus.
• Expertise in data visualization tools such as Power BI, Tableau and Looker is a plus.

Education:

• MS or PhD in data science or related field

Career level: IC-Professional-P4
At McKesson, we care about the well-being of the patients and communities we serve, and that starts with caring for our people. That’s why we have a Total Rewards package that includes comprehensive benefits to support physical, mental, and financial well-being. Our Total Rewards offerings serve the different needs of our diverse employee population and ensure they are the healthiest versions of themselves.
As part of Total Rewards, we are proud to offer a competitive compensation package at McKesson. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered.