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Director Google Data Science Jobs (NOW HIRING)

Apogee Engineering, LLC

Data Scientist

Colorado Springs, CO · On-site

$155K - $190K/yr

Google Data Analytics Professional Certificate; IBM Data Science Professional Certification. Qualifications Minimum Experience: Citizenship: Must be a US citizen Clearance: Must have and be able to ...

Omnicom

Director, Google

New York, NY · On-site

... days are directed by their agency or manager. Our objective is to increase this requirement ... We will process your personal data in accordance with our Recruitment Privacy Notice. Link to ...

Omnicom

Director, Google

New York, NY · Hybrid

... days are directed by their agency or manager. Our objective is to increase this requirement ... We will process your personal data in accordance with our Recruitment Privacy Notice. Link to ...

MCG Health

Director, Data Science

Seattle, WA · On-site

$201K - $281K/yr

The Director, Data Science provides strategic and operational leadership for MCG's Data Science ... Experience developing AI solutions in cloud environments such as AWS, Azure, or Google Cloud ...

Google

Data Engineer, GCS Data Science

New York, NY · On-site

$125K - $150K/yr

Google Customer Solutions (GCS) sales teams are trusted advisors and competitive sellers who ... directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant ...

Google Inc.

Data Engineer, GCS Data Science

Manhattan, NY · On-site

$106 - $151/hr

corporate_fare Google place New York, NY, USA ; Mountain View, CA, USA ; +1 more info_outline X ... directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant ...

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Director Google Data Science information

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$54K

$154.9K

$244K

How much do director google data science jobs pay per year?

As of Aug 20, 2026, the average yearly pay for director google data science in the United States is $154,873.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,000.00 and $189,500.00 per year, depending on experience, location, and employer.

What does a director Google Data Science do?

A Director of Google Data Science leads teams of data scientists, analysts, and engineers to drive data-informed decision-making across the company. They are responsible for setting the strategic vision for data initiatives, overseeing the development of machine learning models and analytics solutions, and collaborating with cross-functional teams to solve complex business problems. This role also involves mentoring staff, managing large-scale projects, and ensuring that data practices align with Google's ethical standards and business goals.

What are the key skills and qualifications needed to thrive as a director Google Data Science?

To thrive as a Director of Google Data Science, you need deep expertise in statistics, machine learning, and data analytics, typically supported by an advanced degree in a quantitative field and significant industry experience. Mastery of programming languages like Python or R, familiarity with big data platforms (such as BigQuery), and experience with cloud computing tools are essential, along with strong project management skills. Outstanding leadership, communication, and strategic vision are crucial soft skills for guiding teams and collaborating with stakeholders across the organization. These skills and qualities are vital for driving impactful data-driven decisions, fostering innovation, and successfully leading large, diverse data science teams.

How does a director Google Data Science typically collaborate with cross-functional teams to drive data-driven decision-making?

As a Director of Google Data Science, you will frequently lead and coordinate with product managers, engineers, designers, and business leaders to translate business goals into actionable data projects. This collaboration involves setting data strategy, defining key metrics, and ensuring that insights are integrated into product roadmaps and business decisions. You’ll also mentor data scientists, facilitate communication between technical and non-technical stakeholders, and help foster a culture of experimentation and innovation. Ensuring alignment across teams and managing priorities is a common challenge, but it’s crucial for maximizing the impact of data science on organizational objectives.

What is the difference between Director Google Data Science vs Data Science Manager?

AspectDirector Google Data ScienceData Science Manager
ResponsibilitiesStrategic leadership, overseeing multiple teams, setting visionTeam management, project execution, day-to-day operations
Required CredentialsAdvanced degrees (Master's/PhD), extensive experience in data scienceBachelor's or Master's, strong technical and leadership skills
Work EnvironmentExecutive level, cross-functional collaboration, strategic planningTeam-focused, project management, technical oversight
Industry UsageCommon in large tech companies, corporate R&D divisionsWidely used across tech, finance, healthcare sectors

The main difference between a Director Google Data Science and a Data Science Manager lies in scope and focus. The Director typically handles strategic planning and oversees multiple teams, while the Manager focuses on project execution and team management. Both roles require strong technical backgrounds, but the Director's role is more executive and vision-oriented.

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Director Google Data Science jobs near you
Infographic showing various Director Google Data Science job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $154,873 per year, or $74.5 per hour.

Data Scientist

Apogee Engineering, LLC

Colorado Springs, CO • On-site

Full-time

Re-posted 14 days ago

Job description

Overview

Apogee is seeking a Data Scientist (DS) to support the U.S. Army Space and Missile Defense Command (USASMDC). This role applies data science, statistics, and automation to mission analytics, helping operational and intelligence teams process large, complex datasets and convert them into actionable insights in support of space and missile defense priorities.

The Data Scientist partners with analysts and technical stakeholders to identify high-value analytic problems, engineer and curate datasets, and develop reproducible pipelines and models to automate workflows and enrich mission data. Responsibilities include data exploration and feature engineering; building and evaluating statistical/ML approaches (as appropriate); developing scripts, tools, and dashboards to support analysis and reporting; and communicating results through clear documentation and briefings. The DS also supports data governance and quality efforts, ensures methods are transparent and repeatable, and transitions solutions into operational use in coordination with Government leads and mission users.

 

This is a full-time opportunity at Petterson Space Force Base (PSFB), CO.

****Contingent Upon Contract Award****

Responsibilities
  • Demonstrate experience and knowledge of computer science concepts, data architecture, intelligence practices, and managing data in a big-data environment.
  • Demonstrate expert knowledge of Python, and Jupyter Notebooks and/or Jupyter Labs.
  • Author cogent and logical scripts using Python and other applicable languages in a virtual environment using common Integrated Development Environments (IDE) such as VS Code, Spyder, PyScript, or Jupyter Notebooks.
  • Develop and use advanced software programs, algorithms, query techniques, models to solve complex intelligence problems, and automated processes to normalize, integrate, and evaluate data.
  • Debug existing and future Python code; refactor legacy code to ensure continued security, functionality, and compatibility.
  • Document and block-comment all code to ensure recoverability and error-checking, and enhance reading, checking, and maintaining code in accordance with common data science and coding standards, such as PEP-8 for Python,5 or using style-guide features embedded in common IDE applications, such as Spyder, VS Code, PyScript or others upon approval by the Government.
  • Collaborate across multi-discipline teams to ensure connectivity between various data sources and business problems.
  • Identify meaningful insights, interpret, and communicate findings, plus make recommendations to stakeholders.
  • Analyze requirements and evaluate technologies for data science capabilities including Natural Language Processing, Machine Learning, predictive modeling, statistical analysis, and hypothesis testing.
  • Maintain awareness of emerging analytics and big-data technologies.
  • Complete required course NSA NETA1400 (Technology Fundamentals for Analysis); recommended completion of any of the following NSA Courses: NETA2402/NETA2108 (Analysis II), RPTG2238, RPTG2235, RPTG3225, RPTG3222 (Basic Analytical Reporting) or equivalent curriculum.
  • Complete recommended certifications: Data Science Council of America (DASCA) certifications, such as Associate Big Data Engineer (ABDE), Associate Big Data Analyst (ABDA), and Senior Data Scientist (SDS); Google Data Analytics Professional Certificate; IBM Data Science Professional Certification.
Qualifications

Minimum Experience:

Citizenship: Must be a US citizen Clearance: Must have and be able to maintain a Top Secret (TS) with Sensitive Compartmented Information (SCI) adjudicationEducation: Bachelors DegreeYears of Experience: 7+ years experience in data science/analytics engineering/software development in big-data environments.

Additional Experience:

  • Expert Python skills; heavy use of Jupyter Notebooks/Labs and common IDEs (e.g., VS Code/Spyder).
  • Proven ability to build and sustain automated data workflows (ingest/normalize/integrate/enrich/evaluate) using algorithms, queries, and models.
  • Strong SDLC skills: debugging, refactoring legacy code, and maintaining secure/compatible codebases.
  • Code quality discipline: clear documentation/block comments and adherence to PEP-8 (or equivalent style enforcement).
  • Working knowledge of data architecture and ability to collaborate across multi-discipline teams to connect data sources to mission problems.
  • Ability to communicate findings and recommendations to stakeholders.
  • Experience applying/evaluating ML/NLP, predictive modeling, and statistical methods (hypothesis testing).
  • NSA NETA1400 (Technology Fundamentals for Analysis) completion, or Government-approved equivalent.

Preferred Qualifications:Additional Experience:

  • NSA courses: NETA2402/NETA2108 and/or RPTG2238/2235/3225/3222 (or equivalent).
  • Certifications: DASCA (ABDE/ABDA/SDS), Google Data Analytics, and/or IBM Data Science.
  • Experience transitioning prototypes into reusable, analyst-ready tools/pipelines and tracking emerging big-data/analytics tech.

Additional InformationLocation: Petterson Space Force Base (PSFB), COOn-siteTravel: 10%

Pay RangeUSD $155,000.00 - USD $190,000.00 /Yr.Employment Type: OTHER

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