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Data Science Supervisor

Pay
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Work setting
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Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting
  • Maintain and evaluate production Agentic AI engines and Python analytics pipelines

  • Keep production databases and enterprise system connections secure and optimized

  • Set best practices for agent observation, evaluation and prompt maintenance

  • Supervise and prioritize the work of direct reports

From the employer’s posting
Lead the ongoing operations, maintenance, and performance evaluation of production Agentic AI engines
Ensure production databases and connections to enterprise systems (such as SAP, Salesforce, and Postgres) are maintained, secure, and highly optimized.
Establish best practices for Agent Observation, Evaluation, and prompt maintenance
Strategize and prioritize responsibilities of direct reports

What you’ll bring

All qualifications

Core experience

  • 6 - 8 years of AI & data science experience preferred, including 2-3 years of direct people management experience (direct people reporting)
  • Excellent communication and storytelling skills (oral, written and presentation)
  • Deep expertise in Google Cloud Platform (GCP) technologies, including Cloud SQL, BigQuery, and GCP Cloud Functions.
  • Ability to work with teams/ stakeholders to drive change/ adoption of analytics solutions
  • Strong knowledge of containerization and orchestration using Kubernetes.
  • Experience integrating and maintaining connections to enterprise databases and applications like Postgres, SAP, and Salesforce.
Qualification wording
6 - 8 years of AI & data science experience preferred, including 2-3 years of direct people management experience (direct people reporting)
Excellent communication and storytelling skills (oral, written and presentation)
Deep expertise in Google Cloud Platform (GCP) technologies, including Cloud SQL, BigQuery, and GCP Cloud Functions.
Ability to work with teams/ stakeholders to drive change/ adoption of analytics solutions
Strong knowledge of containerization and orchestration using Kubernetes.
Experience integrating and maintaining connections to enterprise databases and applications like Postgres, SAP, and Salesforce.
Apply at Cardinal

Posting record

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Status in our records
Live
First seen by us
Aug 10, 202685 days ago
Recorded sightings
160
Last seen by us
Nov 4, 2026
Employer says posted
Jul 15, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 85

Up longer than most. Similar jobs usually come down between day 7 and day 53.

From 7,797 similar postings that came down. Coming down is not always a hire.

Cardinal is hiring

18 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring at a steady pace
  • Takes jobs down quickly
  • 17% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • BigQuery
  • GCP
  • Kubernetes
  • FastAPI
  • Flask
  • PostgreSQL
Where the posting names them
Responsibilities - Lead the ongoing operations, maintenance, and performance evaluation of production Agentic AI engines, FastAPI/Flask services, and Python-based analytical pipelines. - Ensure production databases and connections to enterprise systems (such as SAP, Salesforce, and Postgres) are maintained, secure, and highly optimized.
- Deep expertise in Google Cloud Platform (GCP) technologies, including Cloud SQL, BigQuery, and GCP Cloud Functions. - Advanced proficiency in Python (specifically FastAPI, Flask) and SQL. - Direct experience with Agentic AI architectures, Prompt Engineering, Agent Evaluation, and Agent Observation.
- BTech-BE from Tier 1/2 engineering schools or MStat/MS (Math)/MA Econ/ MS Analytics/data science from Tier 1/2 schools - Deep expertise in Google Cloud Platform (GCP) technologies, including Cloud SQL, BigQuery, and GCP Cloud Functions. - Advanced proficiency in Python (specifically FastAPI, Flask) and SQL.
- Direct experience with Agentic AI architectures, Prompt Engineering, Agent Evaluation, and Agent Observation. - Strong knowledge of containerization and orchestration using Kubernetes. - Experience integrating and maintaining connections to enterprise databases and applications like Postgres, SAP, and Salesforce.
- Lead the ongoing operations, maintenance, and performance evaluation of production Agentic AI engines, FastAPI/Flask services, and Python-based analytical pipelines. - Ensure production databases and connections to enterprise systems (such as SAP, Salesforce, and Postgres) are maintained, secure, and highly optimized. - Establish best practices for Agent Observation, Evaluation, and prompt maintenance to adapt to shifting financial processes and business rules.
- Strong knowledge of containerization and orchestration using Kubernetes. - Experience integrating and maintaining connections to enterprise databases and applications like Postgres, SAP, and Salesforce. - Design ML/LLM pipelines, good knowledge of RAG, prompt engineering.

Your next step

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About the role

We file this job under Data Leadership, by the work the posting describes.

Data leaders run data teams or design how a company's data fits together. Managers hire, set priorities and answer for whether the data work pays off; architects choose the systems and the shape of the data.

Expect years of hands-on data work, experience leading people or projects, and the ability to explain tradeoffs to executives.

Unlike a senior engineer or analyst, most of a data leader's week goes to people, planning and decisions rather than building.

US government figures for computer and information systems managers

Median yearly pay, May 2025
$175,140
Expected change, 2025 to 2035
15.8% more jobsagainst 3.5% for all jobs

The government has no code for data leaders, so these figures are for the closest group, computer and information systems managers, which includes data processing and data operations managers.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 11-3021.

Job description

View original posting ↗

Data Science Supervisor

Headquartered in Dublin, Ohio, Cardinal Health, Inc. (NYSE: CAH) is a global, integrated healthcare services and products company connecting patients, providers, payers, pharmacists and manufacturers for integrated care coordination and better patient management. Backed by nearly 100 years of experience, with more than 50,000 employees in nearly 60 countries, Cardinal Health ranks among the top 20 on the Fortune 500.

Department Overview

AI & Data Science team builds analytics and artificial intelligence solutions that drive success for Cardinal Health by creating material savings, efficiencies and revenue growth opportunities. The team drives business innovation by leveraging emerging technologies and turning them into differentiating business capabilities.

Job Overview

The primary role of the Data Science Supervisor is to oversee the post-deployment operations, continuous optimization, and operational performance of Agentic AI and Intelligent Automation solutions within the Finance Digital Solutions portfolio. This role will lead the operational “Run” phase, ensuring that generative AI agents, Large Language Model (LLM) integrations, and production workflows remain highly available, secure, and accurate. This position collaborates closely with offshore/onshore developers, data scientists, and business partners to manage risk, solve complex problems, and deliver long-term support for mission-critical solutions.

Responsibilities 

  • Lead the ongoing operations, maintenance, and performance evaluation of production Agentic AI engines, FastAPI/Flask services, and Python-based analytical pipelines.
  • Ensure production databases and connections to enterprise systems (such as SAP, Salesforce, and Postgres) are maintained, secure, and highly optimized.
  • Establish best practices for Agent Observation, Evaluation, and prompt maintenance to adapt to shifting financial processes and business rules.
  • Work with cross-functional partners across our highly matrixed organization to understand both upstream inputs to, and downstream impact of, current and future operational processes.
  • Align technical specifications and post-deployment modifications with business needs and enterprise security standard guidelines.
  • Act as a techno-functional leader, generating ideas for process and platform improvements and ensuring data compliance standards are met.
  • Provides direct supervision and leadership to team
  • Strategize and prioritize responsibilities of direct reports
  • Assess business opportunities and promote use of data science, analytics within domain and build internal and external resources and expertise. 
  • A part of the role also requires to be hands-on and working together with external and internal partners to develop, test and operationalize data science and analytical solutions as well as ensure its adoption by businesses.
  • Work to leverage data (Transactional / Big Data, External/ Internal Data, Structured/ Unstructured Data) and analytics methods to develop analytics solutions 


Qualifications

  • 6 - 8 years of AI & data science experience preferred, including 2-3 years of direct people management experience (direct people reporting)
  • BTech-BE from Tier 1/2 engineering schools or MStat/MS (Math)/MA Econ/ MS Analytics/data science from Tier 1/2 schools 
  • Deep expertise in Google Cloud Platform (GCP) technologies, including Cloud SQL, BigQuery, and GCP Cloud Functions.
  • Advanced proficiency in Python (specifically FastAPI, Flask) and SQL.
  • Direct experience with Agentic AI architectures, Prompt Engineering, Agent Evaluation, and Agent Observation.
  • Strong knowledge of containerization and orchestration using Kubernetes.
  • Experience integrating and maintaining connections to enterprise databases and applications like Postgres, SAP, and Salesforce.
  • Design ML/LLM pipelines, good knowledge of RAG, prompt engineering.
  • Monitor system performance, logs, retrieval quality and prompt-effectiveness
  • Integrate microservices with ApigeeX for API management, security (authentication, authorization, rate limiting), monitoring, and analytics.
  • Skills in areas like Agentic AI, GenAI, and some other traditional AI techniques like optimization, Statistics, Machine learning, NLP, Image/ Video, Speech analytics 
  • Preferably good knowledge of Agile & SCRUM development processes 


Soft Skills

  • Coach and Mentor data science operations Team members
  • Excellent communication and storytelling skills (oral, written and presentation) 
  • Highly driven, energetic, flexible & ability to multitask 
  • Ability to work with teams/ stakeholders to drive change/ adoption of analytics solutions 

Candidates who are back-to-work, people with disabilities, without a college degree, and Veterans are encouraged to apply.

Cardinal Health supports an inclusive workplace that values diversity of thought, experience and background. We celebrate the power of our differences to create better solutions for our customers by ensuring employees can be their authentic selves each day. Cardinal Health is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, ancestry, age, physical or mental disability, sex, sexual orientation, gender identity/expression, pregnancy, veteran status, marital status, creed, status with regard to public assistance, genetic status or any other status protected by federal, state or local law.

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