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Director Google Data Science Jobs in Delafield, WI

Master's degree in Data Science, Computer Science, Industrial Engineering, Statistics, or a related field. Certification / License * Certification in data analytics or platforms (e.g., Google Data ...

Collaborate with data scientists, data engineers, business functional and product teams to ... Hands-on experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and AI frameworks (e.g ...

New

Senior MLOps Engineer (Remote)

Menomonee Falls, WI · On-site

$104K - $144K/yr

What You'll Do * Collaborate with Data Scientists and Engineers across the full ML lifecycle ... In-depth knowledge of cloud platform, preferably Google Cloud Platform services, particularly ...

Direct the team through complexity, demonstrating composure through ambiguous, challenging and ... Engineer, Google Professional Cloud Architect, GCP Data Engineer Microsoft Azure Solutions ...

Education in Computer Science, Software Engineering, Data Engineering, Data Science, or a related ... Self-directed problem solver who manages priorities independently. Preferred Qualifications

Education in Computer Science, Software Engineering, Data Engineering, Data Science, or a related ... Self-directed problem solver who manages priorities independently. Preferred Qualifications

Education in Computer Science, Software Engineering, Data Engineering, Data Science, or a related ... Self-directed problem solver who manages priorities independently. Preferred Qualifications

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Showing results 1-20

Director Google Data Science information

See Delafield, WI salary details

$51.8K

$148.5K

$234K

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

As of Aug 21, 2026, the average yearly pay for director google data science in Delafield, WI is $148,545.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,500.00 and $181,800.00 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.

What cities near Delafield, WI are hiring for Director Google Data Science jobs?

Cities near Delafield, WI with the most Director Google Data Science job openings:

Infographic showing various Director Google Data Science job openings in Delafield, WI as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $148,545 per year, or $71.4 per hour.

Data Scientist (Remote)

Kohls Department Stores

Menomonee Falls, WI • On-site

Other

This job post has expired today. Applications are no longer accepted.


Job description

Role Specific Information
Job Description
About the Role
In this role you will work with a data science team and cross-functional partners to solve business challenges and promote data-driven decision making with advanced data analysis and machine learning.
What You'll Do
  • Assist in cleaning, preprocessing and analyzing large datasets to uncover trends, patterns and correlations
  • Conduct exploratory data analysis to cull actionable insights using analytical rigor and statistical methods
  • Collaborate with stakeholders to understand business requirements and translate them into technical solutions
  • Develop and implement statistical and machine learning models to solve business problems within a cross-functional team
  • Collaborate with senior data scientists to fine-tune, optimize and ensure the scalability of models and algorithms
  • Document projects, including business objectives, data gathering and processing, leading approaches, final algorithm, detailed set of results and analytical metrics
  • Identify and drive continuous improvement of key business metrics within the balanced team
  • Remain current on the latest trends and developments in data science and technology through self-learning and training opportunities
  • Additional tasks may be assigned

Addendum
DECISION SCIENCE
Accountabilities
  • Begin to understand business challenges and their conversion into optimization problems, focusing on defining objectives and adhering to business constraints such as budget limitations and sell-through rates
  • Contribute to large-scale optimization and statistical analysis in web analytics, forecasting, supply chain management, pricing and inventory management
  • Contribute to the tuning of models by adjusting objective functions, constraints, etc.

Skills & Experience
  • Experience using commercial or open-source optimization tools such as Gurobi, Pyomo, CPLEX, etc
  • BS in Operations Research, Data Science, Computer Science, Machine Learning, Applied Mathematics, or equivalent quantitative field

What Skills You Have
Required
  • Experience developing state-of-the-art algorithms using machine learning, statistical and optimization methods to power various aspects of highly complex business models and deliver value
  • Experience using modern analytics tools, programming languages, and cloud platforms such as Python, R, Spark, SQL, Google Cloud Platform, etc.
  • Strong problem-solving skills with an emphasis on product development
  • Experience proposing rapid experiments to test the effectiveness of new strategies or initiatives and iterate quickly based on results
  • Effective communication and collaboration skills
  • Bachelor's of Science in Data Science, Computer Science, Statistics, Applied Mathematics or equivalent quantitative field
  • 2+ years of progressively complex data science or analytics experience

Preferred
  • Master's degree
  • Retail experience
  • Supply chain management
  • Marketing models
  • Logistics experience

Essential Functions
The requirements listed below are representative of functions you will be required to perform, however you may be required to perform additional functions. Kohl's may revise this job description at any time. To perform this job successfully, you must be able to perform each essential function satisfactorily. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions, absent undue hardship.
  • Ability to perform the accountabilities listed in the "What You'll Do" Section
  • Ability to comply with dress code requirements
  • Basic math and reading skills, legible handwriting, and basic computer operation
  • Ability to maintain prompt and regular attendance and meet scheduling requirements as set by the company
  • Ability to learn and comply with all company policies, procedures, standards and guidelines
  • Ability to receive, understand and proactively respond to direction from leadership and other company personnel
  • Ability to work as part of a team and interact effectively and appropriately with others
  • Ability to maintain composure and work in a fast paced environment while accomplishing multiple tasks within established timeframes
  • Ability to satisfactorily complete company training programs
  • Ability to use a personal computer for tasks such as communicating, preparing reports, etc.
  • Ability to plan, prioritize and monitor activities across business units
  • Ability to complete or oversee the completion of assigned projects in a timely manner