Senior Manager, Data Science

Johnson & Johnson

Confirmed live 2 days ago High trust
Closes in 3 days Hybrid

Quick summary

Work type
Hybrid
Location
Raynham, MAWest Chester, PAPalm Beach Gardens, FLWarsaw, INRaritan, NJ
Salary
$137,000–$235,750 / yr
Employment
Full-time
Posted
4 days ago
Freshness
Confirmed live 2 days ago
Closes
Oct 30, 2026 (soon)

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $187k
This role $186k
$124k $248k
below market most similar roles pay here above market

This role pays more than 54% of similar roles. Most pay $159,000–$214,900 — the blue band above. At the midpoint, this role pays about $186k versus about $187k for comparable roles.

Based on 240 similar postings.

Employer

About Johnson & Johnson

Johnson & Johnson is a multinational corporation operating in three main segments: consumer health products, pharmaceuticals, and medical devices, known for brands like Tylenol, Band-Aid, and Janssen. Industry: Pharmaceuticals & Medical Devices

Johnson & Johnson currently has 45 open roles on FindRole.

Listed pay typically runs $109,000–$201,250 across 37 roles with salary data.

Most-posted roles

View all roles at Johnson & Johnson

At a glance

TL;DR · Senior Manager, Data Science

JOB TITLE: Senior Manager, Data Science The Senior Manager, Data Science leads a team within the Finance department to advance data science, artificial intelligence, and analytics capabilities. This leader manages a portfolio of initiatives to develop scalable, business-focused solutions that improve forecasting and strengthen decision-making across Account to Report, Procure to Pay, and Invoice to Cash processes. The role involves guiding model development, validation, and deployment while establishing standards for model governance and responsible AI in a regulated environment. Key technical requirements include proficiency in Python, R, SQL, machine learning, statistical modeling, cloud data platforms, and business intelligence tools. The position requires translating complex financial and operational data into actionable insights, utilizing MLOps, intelligent automation, and enterprise data architectures to drive efficiency and accuracy across global finance priorities.

What does a Data Science Manager earn?

Median $211200 from 43 postings across 13 companies.

See salary data

What you'll do

  • Lead a portfolio of data science, AI, and advanced analytics initiatives aligned with Finance priorities.
  • Manage forecasting initiatives by guiding solution design, model development, validation, deployment, and performance monitoring.
  • Improve efficiency and accuracy of A2R, P2P, and I2C processes through automation and AI.
  • Translate business needs into clear analytical roadmaps and scalable solutions with cross-functional stakeholders.
  • Oversee the development of analytical products that convert complex financial data into actionable insights.
  • Manage, coach, and develop a team of data scientists to foster technical excellence and accountability.
  • Establish standards for model governance, data quality, documentation, and responsible AI in a regulated environment.
  • Drive adoption of AI solutions by embedding them into business processes and measuring their impact.

What we're looking for

  • Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Finance, Economics, or a related quantitative field.
  • Master’s degree in Data Science, Statistics, Computer Science, Business Analytics, Finance, or a related discipline (preferred).
  • Typically 6-8 years of progressive experience in data science, advanced analytics, machine learning, or related quantitative roles.
  • Experience leading people and complex analytical workstreams, including managing and mentoring data science and analytics professionals.
  • Demonstrated experience developing and operationalizing forecasting, predictive modeling, optimization, or other advanced analytics solutions.
  • Strong proficiency in Python or R, SQL, machine learning, statistical modeling, cloud data platforms, and business intelligence tools.
  • Strong understanding of finance processes, specifically Account to Report (A2R), Procure to Pay (P2P), and Invoice to Cash (I2C).
  • Experience applying data science and AI within Finance in a global, highly regulated environment (preferred).

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