Data Scientist

About the Role

Key Responsibilities

• Perform advanced analytics functions (e.g., XGBoost, SVM, Random Forest, Cluster Analysis) to create insights that provide meaningful results.
• Design and implement algorithms for object detection, recognition, tracking, natural language processing (NLP), text generation, and language translation.
• Leverage techniques like Retrieval Augmented Generation (RAG) to align large language models (LLMs) to specific use cases.
• Develop inventory optimization and multi-echelon simulation frameworks for supply chain, including building time series models using Sarima, Prophet, Holt-Winters, and Transformers.
• Extract, analyze, and interpret large volumes of structured and unstructured data from various sources.
• Design and execute experiments to test hypotheses and validate models.
• Collaborate with engineering teams to automate machine learning models and develop comprehensive documentation.
• Build prototypes for rapid delivery to understand different business solutions.
• Work within an agile framework.
• Develop an A/B testing framework by conducting hypothesis-driven tests to enhance products and services.
• Familiarity with data engineering concepts such as data ingestion, ETL, and data modeling to ensure efficient data pipelines in Databricks.
• Present findings and insights to non-technical stakeholders in a clear and concise manner.
• Assist in developing and maintaining long-term stakeholder relationships and networks.

Requirements

• Degree or equivalent and typically requires 4+ years of relevant experience.
• Strong SQL skills.
• Proven experience with MLOps processes.
• Experience in data wrangling, statistical methods, and machine learning techniques such as SVM, gradient boosting, k-means, reinforcement learning, and multivariate testing.
• Ability to communicate technical concepts to non-technical audiences.
• Ability to work both independently and collaboratively in a fast-paced environment.

Nice to Have

• Bachelor's degree in a technical field such as Computer Science, Statistics, Applied Mathematics, Finance, Economics or related STEM majors; Master’s and/or PhD preferred.
• 3+ years data science, analytics, or programming experience based on industry and academic background.
• Experience with Azure, Snowflake, Databricks, Python.
• Experience with data engineering concepts like data ingestion, ETL, and data modeling in the cloud.
• Hands-on experience with statistical methods and machine learning including reinforcement learning and multivariate testing.
• Experience with Databricks notebooks, clusters, and job scheduling.

Qualifications

• Bachelor’s degree in a relevant technical field; Master’s or PhD preferred.
• 4+ years of relevant experience in data science or analytics.

Benefits & Perks

• Competitive compensation package as part of Total Rewards.
• Potential for annual bonus or long-term incentive opportunities.
• Pay range: $104,600 - $174,400, aligned with McKesson’s pay philosophy.
• Additional benefits detailed on McKesson’s benefits page.