1

Director Google Data Science Jobs in Indiana (NOW HIRING)

... direct current (DC) systems, and associated power management or Supervisory Control and Data ... We empower Google customers with breakthrough capabilities and insights by delivering AI and ...

Manage projects and direct work of more junior team members. * Six (6) or more years of data science/predictive analytics experience in insurance or eight (8+) or more years predictive modeling ...

Data Architect

Indianapolis, IN · On-site

$61 - $78.50/hr

Bachelor's degree in Computer Science, Information Systems, Data Science, or a related field * 8+ ... Experience with cloud platforms such as AWS, Microsoft Azure, and/or Google Cloud Platform

Data Architect

Zionsville, IN

$61.75 - $79.50/hr

Bachelor's degree in Computer Science, Information Systems, Data Science, or a related field * 8+ ... Experience with cloud platforms such as AWS, Microsoft Azure, and/or Google Cloud Platform

Manage projects and direct work of more junior team members. * Six (6) or more years of data science/predictive analytics experience in insurance or eight (8+) or more years predictive modeling ...

Showing results 41-60

Director Google Data Science information

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 are popular job titles related to Director Google Data Science jobs in Indiana?

For Director Google Data Science jobs in Indiana, the most frequently searched job titles are:

What job categories do people searching Director Google Data Science jobs in Indiana look for?

The top searched job categories for Director Google Data Science jobs in Indiana are:

What cities in Indiana are hiring for Director Google Data Science jobs?

Cities in Indiana with the most Director Google Data Science job openings:

Infographic showing various Director Google Data Science job openings in Indiana as of August 2026, with employment types broken down into 1% As Needed, 86% Full Time, 11% Part Time, and 2% Contract. Highlights an 83% Physical, 5% Hybrid, and 12% Remote job distribution.

Data Scientist (Statistician) - Direct Hire

US Department of the Treasury

Evansville, IN • On-site

$125K/yr

Full-time

Posted 8 days ago


U.S. Department Of The Treasury rating

8.2

Company rating: 8.2 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

311th of 855 rated public administrative organizations


Job description

WHAT IS LARGE BUSINESS AND INTERNATIONALDIVISION?
A description of the business units can be found at: https://www.jobs.irs.gov/about/who/business-divisions

  • Position is to be filled in the following area(s):
    • LBI - ADCCI - Assistant Deputy Commissioner Compliance Integration.


REVIEW THE ADDITIONAL INFORMATION BELOW FOR FURTHER DETAILS

Qualifications:Federal experience is not required. Experience may have been gained in the public sector, private sector or through Volunteer Service. One year of experience refers to full-time work; part-timework is considered on a prorated basis. To ensure full credit for your work experience, please indicate dates of employment by month/day/year, and indicate number of hours worked per week, on your resume.
You must meet the following requirements by the closing date of this announcement.
QUALIFICATION REQUIREMENTS: To qualify for this position, you must meet the qualification requirements outlined below:
BASIC REQUIREMENTS (IOR) ALL GRADES:
EDUCATION: A degree that included 15 semester hours in statistics (or in mathematics and statistics, provided at least 6 semester hours were in statistics), and 9 additional semester hours in one or more of the following: physical or biological sciences, medicine, education, or engineering; or in the social sciences including demography, history, economics, social welfare, geography, international relations, social or cultural anthropology, health sociology, political science, public administration, psychology, etc. Credit toward meeting statistical course requirements should be given for courses in which 50 percent of the course content appears to be statistical methods, e.g., courses that included studies in research methods in psychology or economics such as tests and measurements or business cycles, or courses in methods of processing mass statistical data such as tabulating methods or electronic data processing.
OR
COMBINATION OF EDUCATION AND EXPERIENCE: Combination of education and experience includes courses as shown in A above, plus appropriate experience or additional education. The experience should have included a full range of professional statistical work such as (a) sampling, (b) collecting, computing, and analyzing statistical data, and (c) applying statistical techniques such as measurement of central tendency, dispersion, skewness, sampling error, simple and multiple correlation, analysis of variance, and tests of significance.
AND
SPECIALIZED EXPERIENCE GS-14: In addition to meeting basic requirements, to be eligible for this position at this grade level, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-13 grade level in the Federal service.
Specialized experience for this position includes:
  • Experience identifying and assessing the validity and reliability of relevant data sources and retrieving structured and unstructured data in multiple types and formats, including Extensible Markup Language (XML) files and large datasets, for use in data science projects.
  • Experience cleaning, transforming, combining, and integrating structured and unstructured data from multiple sources, including identifying and resolving missing values, outliers, and duplicate records, to prepare data for analysis.
  • Experience applying data-mining process models, including the Cross-Industry Standard Process for Data Mining (CRISP-DM) or Sample, Explore, Modify, Model, Assess (SEMMA), to collect, prepare, analyze, and evaluate data during data science projects.
  • Experience applying statistical methods, probability, statistical inference, hypothesis testing, experimental design, forecasting, and sampling methods to analyze data, evaluate results, and support program or business decisions.
  • Experience developing and evaluating analytical and artificial intelligence models using machine learning, text analytics, natural language processing, large language models, graph theory, link analysis, optimization models, complex adaptive systems, or deep-learning neural networks.
  • Experience using programming languages, query languages, data-intelligence platforms, and data-storage technologies, including R, Python, Structured Query Language (SQL), Java, Databricks, Sybase, Oracle, or open-source databases, to retrieve, process, query, analyze, and integrate data during data science projects.
  • Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing technical deliverables for validity and reliability; and communicating analytical findings, model results, limitations, conclusions, and recommendations to technical and nontechnical stakeholders through written products, presentations, graphs, tables, charts, or business-intelligence products.

AND
You must also meet the following requirements:
  • MINIMUM AGE REQUIREMENT: Minimum age for federal employment is 18 years old, or at least 16 years old and have:
    • Graduated from high school or been awarded a certificate equivalent to graduating from high school; or
    • Completed a formal vocational training program; or
    • Received a statement from school authorities agreeing with your preference for employment rather than continuing your education

For more information on qualifications please refer to OPM's Qualifications Standards.Education:A college or university degree generally must be from an accredited (or pre-accredited) college or university recognized by the U.S. Department of Education. For a list of schools which meet these criteria, please refer to Department of Education Accreditation page.
FOREIGN EDUCATION: Education completed in foreign colleges or universities may be used to meet the requirements. You must show proof the education credentials have been deemed to be at least equivalent to that gained in conventional U.S. education program. It is your responsibility to provide such evidence when applying. Click here (Section 3, Explanation of Terms) or here for Foreign Education Credentialing instructions.
We recommend choosing an evaluator from a member organization of one of the following national associations of credential evaluation services: National Association of Credential Evaluation Services (NACES) or Association of International Credentials Evaluators (AICE).Employment Type: OTHER

What U.S. Department Of The Treasury employees say

Pay

Hours and flexibility

Workplace

Get the full story on Breakroom