McKesson’s Corporate
Senior Data Scientist
McKesson’s Corporate, Richmond, Virginia, United States, 23214
Your Consent
Responsibilities:
Analyze large and complex datasets to uncover patterns, trends, and insights that can improve business performance and decision-making.
Develop predictive models, machine learning algorithms, and statistical models to solve complex business challenges.
Collaborate with cross-functional teams to understand business requirements and develop data-driven solutions.
Design and execute experiments to test hypotheses and validate models.
Apply advanced statistical techniques and data mining algorithms to extract actionable insights from structured and unstructured data.
Build and maintain scalable data pipelines and data processing systems.
Communicate findings and recommendations to stakeholders, including non-technical audience, through visualizations, reports, and presentations.
Stay updated on advancements in data science, machine learning, and analytics.
Strong focus on delivery and Agile methodologies, leading projects from conception to implementation.
Collaborate with the Enterprise Analytics team to integrate new practices and technologies.
Minimum Requirements:
Typically requires 10+ years of hands-on work experience developing and applying advanced analytics solutions in a corporate environment.
Critical Skills:
Hands-on experience building and delivering Enterprise Data Solutions.
Extensive professional experience with Big Data systems, data pipelines, and data processing.
Familiarity with data privacy standards, methodologies, and best practices.
Practical hands-on experience with data technologies and Cloud Platforms like Hadoop, Hive, Redshift, Big Query, Snowflake, Databricks, GCP, and Azure.
Hands-on experience working on analytical platforms like SAS, R, Python, Azure ML.
Expertise in Unix Shell scripting and Dependency driven job schedulers.
Expertise in Data visualization tools such as Power BI, Tableau, and Looker is a plus.
Ability to understand API Specs, identify relevant API calls, extract data and implement data pipelines & SQL friendly data structures.
Additional Skills:
Excellent communication and interpersonal skills, with the ability to engage and influence technical teams, business leaders, and external partners.
Strategic thinker with a strong analytical mindset and problem-solving abilities.
Proven track record as a Data Scientist, delivering data-driven solutions to complex business challenges.
Demonstrated expertise in building and deploying AI/Machine Learning solutions at scale.
Proficient in programming languages such as Python or R, and experience with data manipulation and analysis libraries (e.g., Pandas, NumPy, scikit-learn).
Strong knowledge of statistical techniques, machine learning algorithms, and data mining techniques.
Proficient in applied analytical techniques - clustering, regression analysis, time series analysis, NLP, neural networks, KNN, association rules, decision trees, logistic regression or similar.
Positive and flexible attitude to enable adjusting to different needs in an ever-changing environment.
Experience with data in the drug supply chain and commercial domain within healthcare, pharma is a plus.
Highly influential and ability to educate stakeholders on the role of data and its purpose in the business.
Teams up and collaborates for speed, agility, delivery excellence, and innovation.
Strong negotiation and decision-making skills.
Education:
Bachelor’s or master’s degree in computer science, Data Science, Information Technology, or a related field OR equivalent experience.
Compensation:
Our Base Pay Range for this position: $124,200 - $207,000.
McKesson is an Equal Opportunity Employer. McKesson provides equal employment opportunities to applicants and employees and is committed to a diverse and inclusive environment.
Join us at McKesson!
#J-18808-Ljbffr
Responsibilities:
Analyze large and complex datasets to uncover patterns, trends, and insights that can improve business performance and decision-making.
Develop predictive models, machine learning algorithms, and statistical models to solve complex business challenges.
Collaborate with cross-functional teams to understand business requirements and develop data-driven solutions.
Design and execute experiments to test hypotheses and validate models.
Apply advanced statistical techniques and data mining algorithms to extract actionable insights from structured and unstructured data.
Build and maintain scalable data pipelines and data processing systems.
Communicate findings and recommendations to stakeholders, including non-technical audience, through visualizations, reports, and presentations.
Stay updated on advancements in data science, machine learning, and analytics.
Strong focus on delivery and Agile methodologies, leading projects from conception to implementation.
Collaborate with the Enterprise Analytics team to integrate new practices and technologies.
Minimum Requirements:
Typically requires 10+ years of hands-on work experience developing and applying advanced analytics solutions in a corporate environment.
Critical Skills:
Hands-on experience building and delivering Enterprise Data Solutions.
Extensive professional experience with Big Data systems, data pipelines, and data processing.
Familiarity with data privacy standards, methodologies, and best practices.
Practical hands-on experience with data technologies and Cloud Platforms like Hadoop, Hive, Redshift, Big Query, Snowflake, Databricks, GCP, and Azure.
Hands-on experience working on analytical platforms like SAS, R, Python, Azure ML.
Expertise in Unix Shell scripting and Dependency driven job schedulers.
Expertise in Data visualization tools such as Power BI, Tableau, and Looker is a plus.
Ability to understand API Specs, identify relevant API calls, extract data and implement data pipelines & SQL friendly data structures.
Additional Skills:
Excellent communication and interpersonal skills, with the ability to engage and influence technical teams, business leaders, and external partners.
Strategic thinker with a strong analytical mindset and problem-solving abilities.
Proven track record as a Data Scientist, delivering data-driven solutions to complex business challenges.
Demonstrated expertise in building and deploying AI/Machine Learning solutions at scale.
Proficient in programming languages such as Python or R, and experience with data manipulation and analysis libraries (e.g., Pandas, NumPy, scikit-learn).
Strong knowledge of statistical techniques, machine learning algorithms, and data mining techniques.
Proficient in applied analytical techniques - clustering, regression analysis, time series analysis, NLP, neural networks, KNN, association rules, decision trees, logistic regression or similar.
Positive and flexible attitude to enable adjusting to different needs in an ever-changing environment.
Experience with data in the drug supply chain and commercial domain within healthcare, pharma is a plus.
Highly influential and ability to educate stakeholders on the role of data and its purpose in the business.
Teams up and collaborates for speed, agility, delivery excellence, and innovation.
Strong negotiation and decision-making skills.
Education:
Bachelor’s or master’s degree in computer science, Data Science, Information Technology, or a related field OR equivalent experience.
Compensation:
Our Base Pay Range for this position: $124,200 - $207,000.
McKesson is an Equal Opportunity Employer. McKesson provides equal employment opportunities to applicants and employees and is committed to a diverse and inclusive environment.
Join us at McKesson!
#J-18808-Ljbffr