Senior Manager, Data Science

GitLab

Confirmed live today High trust
Remote

Quick summary

Work type
Remote
Location
Remote
Salary
$152,800–$259,200 / yr
Posted
5 days ago
Freshness
Confirmed live today

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $185k
This role $206k
$120k $274k
below market most similar roles pay here above market

This role pays more than 65% of similar roles. Most pay $155,075–$214,900 — the blue band above. At the midpoint, this role pays about $206k versus about $185k for comparable roles.

Based on 240 similar postings.

Employer

About GitLab

GitLab is an all-remote software company that develops an AI-powered DevSecOps platform combining source code management, CI/CD, security scanning, and project planning in a single application.

GitLab currently has 48 open roles on FindRole.

Listed pay typically runs $152,800–$248,600 across 42 roles with salary data.

Most-posted roles

View all roles at GitLab

At a glance

TL;DR · Senior Manager, Data Science

The Senior Manager, Data Science leads the Product Data Science team within the data organization. This role involves managing a team of six data scientists to drive product impact, set the analytical agenda, and define excellence for a merged data science function. Responsibilities include setting long-range roadmaps, owning prioritization across product areas, and partnering with Product and Engineering leaders on complex questions. The successful candidate will build production models, conduct experiments, and manage team growth. Required skills include deep expertise in statistics, causal inference, and experimentation, alongside proficiency in SQL, Python, and Snowflake. The role addresses the business problem of determining what to build, measuring feature success, and understanding customer value within a DevSecOps and AI-powered product environment.

What does a Data Science Manager earn?

Median $211200 from 44 postings across 12 companies.

See salary data

What you'll do

  • Set a long-range vision and roadmap for Product Data Science aligned with company strategy.
  • Own prioritization and trade-offs across product areas while adapting the team to shifting priorities.
  • Partner with Product and Engineering leaders to solve complex questions using experiments or production models.
  • Hire, coach, and retain a high-performing team by building career paths and providing regular feedback.
  • Establish standards for experimentation, causal inference, metric definition, and production modeling.
  • Identify risks and resource gaps early to provide senior leaders with clear options for timely decisions.
  • Perform hands-on tasks including reviewing models, pressure-testing analyses, and writing SQL queries.

What we're looking for

  • 10+ years in data science, product analytics, or a related field.
  • 3+ years managing data science or analytics teams in B2B SaaS or tech.
  • Deep expertise in statistics and experimentation, including quasi-experimental methods like difference-in-differences and synthetic control.
  • Expert SQL (Snowflake preferred) and strong Python with experience taking ML models to production.
  • Fluent with AI tools and sound judgment on when AI output can be trusted.
  • Strong product sense and a track record as a trusted partner to Product and Engineering leaders.
  • Exceptional communication skills to make complex problems and findings clear to any audience.
  • Advanced degree in a quantitative field (preferred).

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