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Data Science Major Jobs in Indiana (NOW HIRING)

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Data Science Major information

What are the key skills and qualifications needed to thrive as a Data Science Major, and why are they important?

To thrive as a Data Science Major, you need a solid understanding of mathematics, statistics, and programming languages such as Python or R, typically backed by coursework or a related degree. Familiarity with data analysis tools, machine learning libraries, and platforms like SQL, TensorFlow, or Jupyter Notebook is also important. Critical thinking, effective communication, and problem-solving skills help you interpret data insights and collaborate on projects. These competencies enable you to extract meaningful information from data, drive decision-making, and succeed in a data-driven environment.

What types of projects or problems do Data Science majors typically work on during internships or entry-level roles?

Data Science majors in internships or entry-level positions often collaborate on projects involving data cleaning, exploratory data analysis, and building predictive models. They might work with real-world datasets to identify trends, automate reporting, or support business decision-making with data-driven insights. These roles typically require teamwork with software engineers, business analysts, and domain experts, offering valuable opportunities to apply classroom knowledge to practical challenges and to develop skills in popular tools like Python, R, and SQL.

What is a Data Science major?

A Data Science major is an academic program that focuses on teaching students how to collect, analyze, and interpret large sets of data to solve real-world problems. It combines coursework in statistics, computer science, mathematics, and domain-specific knowledge to prepare graduates for roles in various industries such as technology, healthcare, finance, and more. Students learn programming languages like Python or R, machine learning techniques, and data visualization skills. The major often includes hands-on projects and internships to provide practical experience in analyzing and extracting insights from data.

What is the difference between Data Science Major vs Data Analyst?

AspectData Science MajorData Analyst
Required CredentialsDegree in Data Science, Computer Science, or related fieldsDegree in Statistics, Mathematics, or related fields
Work EnvironmentResearch, development, and complex data modelingData interpretation, reporting, and visualization
Industry UsageTech companies, finance, healthcare, academiaBusiness, marketing, finance, healthcare
Common Search/ComparisonData Science Major vs Data Analyst

While both roles involve working with data, a Data Science Major typically prepares individuals for complex data modeling, machine learning, and research tasks. In contrast, a Data Analyst focuses on interpreting data, creating reports, and visualizations to support business decisions. The roles often overlap, but the Data Science Major emphasizes advanced analytics and programming skills, whereas Data Analysts concentrate on data interpretation and communication.

What are popular job titles related to Data Science Major jobs in Indiana? For Data Science Major jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Data Science Major jobs in Indiana look for? The top searched job categories for Data Science Major jobs in Indiana are:
What cities in Indiana are hiring for Data Science Major jobs? Cities in Indiana with the most Data Science Major job openings:
Infographic showing various Data Science Major job openings in Indiana as of May 2026, with employment types broken down into 1% As Needed, 61% Full Time, 35% Part Time, and 3% Contract. Highlights an 91% Physical, 2% Hybrid, and 7% Remote job distribution.
Data Science Manager, Gen AI - SFL Scientific

Data Science Manager, Gen AI - SFL Scientific

Deloitte

Indianapolis, IN

Other

Posted 9 days ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 86 frontline employees who took The Breakroom Quiz

59th of 138 rated financial services


Job description

Our Deloitte Strategy & Transactions team helps guide clients through their most critical moments and transformational initiatives. From strategy to execution, this team delivers integrated, end-to-end support and advisory services covering valuation modeling, cost optimization, restructuring, business design and transformation, infrastructure and real estate, mergers and acquisitions (M&A), and sustainability. Work alongside clients every step of the way, helping them navigate new challenges, avoid financial pitfalls, and provide practical solutions at every stage of their journey-before, during, and after any major transformational projects or transactions.
SFL Scientific is a Deloitte Business that is part of our Strategy Offering, within our broader Strategy & Transactions practice mentioned above. This specialized team brings together several key capabilities to architect integrated programs that transform our clients' businesses. We are hiring a Data Science Manager to support the technical design, development, and deployment of novel AI solutions across healthcare, life sciences, manufacturing, consumer, energy, and other industries. Join us at SFL Scientific to expand your technical acumen through the lens of professional services and consulting and help create novel solutions to advance your data science & AI career.

Recruiting for this role ends on 8/31/2026.

Work You'll Do
As a Data Science Manager at SFL Scientific, you will develop and manage a team of developers to deliver novel solutions in the AI and GenAI domains. You will be responsible for the technical direction of client engagements while defining the project strategy, communicating complex concepts to both technical and non-technical audiences, and leading solution development to solve our clients' use cases. The Data Science Manager will provide leadership for our comprehensive data science and AI initiatives, developing and executing strategies that deliver measurable business and scientific outcomes. Successful candidates will be an expert in using state-of-the-art technologies such as computer vision, natural language processing (NLP), time-series analysis, graph neural networks, and other AI/ML subdomains to solve complex business problems across diverse applications and use cases. Data Science Managers are also responsible for but not limited to: 

  • Support identification of high-value AI opportunities that drive industry advantage, representing an organization's AI vision through strategic delivery and industry.
  • Serve as the technical lead on projects to drive the technical strategy, roadmap, and prototyping of AI/ML solutions to meet each clients' unique requirements
  • Engage and guide a diverse set of clients with high autonomy in AI strategy and adoption, including understanding organizational needs, performing exploratory data analysis (EDA), building and validating models, and deploying models into production
  • Lead comprehensive AI initiatives spanning predictive and generative AI, overseeing development of advanced models and ensuring systems are scalable, efficient, and adhere to requirements and AI guidelines
  • Support an interdisciplinary team of data scientists, engineers, and solution architects to achieve technical delivery objectives and real-world performance for production and research applications
  • Lead in the research and adoption of industry best practices for validation and deployment of models; support best delivery practices, code review, UAT, unit, and integration tests
  • Present to key stakeholders, including solution findings and options for potential deployment infrastructure, hardware, software, cloud, etc.
  • Mentor, motivate, and coach junior data scientists on technical best practices and inspire professional development
  • Develop key skillsets and delivery experience to grow into leadership or non-technical management and business roles

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to mentor and provide clear guidance to others

The Team
Our Strategy offering architects bold strategies to achieve business and mission goals, enabling growth, competitive advantage, technology modernization, and continuous digital and AI transformation.

Specifically, SFL Scientific, a Deloitte Business, is a data science professional services practice focused on strategy, technology, and solving business challenges with Artificial Intelligence (AI). The team has a proven track record serving large, market-leading organizations in the private and public sectors, successfully delivering high-quality, novel and complex projects, and offering deep domain and scientific capabilities. We are advancing both predictive and generative AI technologies while maintaining a commitment to data-driven decision making across all levels of a client's organization, building solutions that drive growth and create meaningful impact. Made up of experienced AI strategists, data scientists, and AI engineers, they serve as trusted advisors to executives, helping them understand and evaluate new and essential areas for AI investment and identify unique opportunities to transform their businesses.

Qualifications

Required:

  • Master's or PhD degree in a relevant STEM field (Data Science, Computer Science, Engineering, Mathematics, Physics, etc.)
  • 6+ years of experience working in data science, data engineering, software engineering, or MLOps
  • 6+ years of experience in AI/ML algorithm development workflow and data analysis in the major data modalities from NLP, time-series analysis, computer vision to graph models
  • 6+ years of experience in core programming languages and data science packages (Python, Keras, PyTorch, Pandas, Scikit-learn, Docker, Kubernetes, etc.)
  • 6+ years of experience with traditional ML and deep learning techniques (CNNs, RNNs, LSTMs, GANs), model tuning, and validation of developed algorithms
  • 4+ years of experience managing teams and delivering complex and critical projects
  • Live within commuting distance to one of Deloitte's consulting offices
  • Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred:

  • Experience with cloud deployment (AWS, Azure, GCP), such as building and scaling in AWS SageMaker or Azure ML Studio
  • Experience with developing and testing GenAI solutions
  • Experience in a client-facing role or internal AI product development role
  • Highly proficient written and verbal skills to support briefings, proposals, technical sprint plans, solution reports, progress updates, and executive presentations

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $155,600 to $306,800.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Qualifications:

Our Deloitte Strategy & Transactions team helps guide clients through their most critical moments and transformational initiatives. From strategy to execution, this team delivers integrated, end-to-end support and advisory services covering valuation modeling, cost optimization, restructuring, business design and transformation, infrastructure and real estate, mergers and acquisitions (M&A), and sustainability. Work alongside clients every step of the way, helping them navigate new challenges, avoid financial pitfalls, and provide practical solutions at every stage of their journey-before, during, and after any major transformational projects or transactions.
SFL Scientific is a Deloitte Business that is part of our Strategy Offering, within our broader Strategy & Transactions practice mentioned above. This specialized team brings together several key capabilities to architect integrated programs that transform our clients' businesses. We are hiring a Data Science Manager to support the technical design, development, and deployment of novel AI solutions across healthcare, life sciences, manufacturing, consumer, energy, and other industries. Join us at SFL Scientific to expand your technical acumen through the lens of professional services and consulting and help create novel solutions to advance your data science & AI career.

Recruiting for this role ends on 8/31/2026.

Work You'll Do
As a Data Science Manager at SFL Scientific, you will develop and manage a team of developers to deliver novel solutions in the AI and GenAI domains. You will be responsible for the technical direction of client engagements while defining the project strategy, communicating complex concepts to both technical and non-technical audiences, and leading solution development to solve our clients' use cases. The Data Science Manager will provide leadership for our comprehensive data science and AI initiatives, developing and executing strategies that deliver measurable business and scientific outcomes. Successful candidates will be an expert in using state-of-the-art technologies such as computer vision, natural language processing (NLP), time-series analysis, graph neural networks, and other AI/ML subdomains to solve complex business problems across diverse applications and use cases. Data Science Managers are also responsible for but not limited to: 

  • Support identification of high-value AI opportunities that drive industry advantage, representing an organization's AI vision through strategic delivery and industry.
  • Serve as the technical lead on projects to drive the technical strategy, roadmap, and prototyping of AI/ML solutions to meet each clients' unique requirements
  • Engage and guide a diverse set of clients with high autonomy in AI strategy and adoption, including understanding organizational needs, performing exploratory data analysis (EDA), building and validating models, and deploying models into production
  • Lead comprehensive AI initiatives spanning predictive and generative AI, overseeing development of advanced models and ensuring systems are scalable, efficient, and adhere to requirements and AI guidelines
  • Support an interdisciplinary team of data scientists, engineers, and solution architects to achieve technical delivery objectives and real-world performance for production and research applications
  • Lead in the research and adoption of industry best practices for validation and deployment of models; support best delivery practices, code review, UAT, unit, and integration tests
  • Present to key stakeholders, including solution findings and options for potential deployment infrastructure, hardware, software, cloud, etc.
  • Mentor, motivate, and coach junior data scientists on technical best practices and inspire professional development
  • Develop key skillsets and delivery experience to grow into leadership or non-technical management and business roles

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to mentor and provide clear guidance to others

The Team
Our Strategy offering architects bold strategies to achieve business and mission goals, enabling growth, competitive advantage, technology modernization, and continuous digital and AI transformation.

Specifically, SFL Scientific, a Deloitte Business, is a data science professional services practice focused on strategy, technology, and solving business challenges with Artificial Intelligence (AI). The team has a proven track record serving large, market-leading organizations in the private and public sectors, successfully delivering high-quality, novel and complex projects, and offering deep domain and scientific capabilities. We are advancing both predictive and generative AI technologies while maintaining a commitment to data-driven decision making across all levels of a client's organization, building solutions that drive growth and create meaningful impact. Made up of experienced AI strategists, data scientists, and AI engineers, they serve as trusted advisors to executives, helping them understand and evaluate new and essential areas for AI investment and identify unique opportunities to transform their businesses.

Qualifications

Required:

  • Master's or PhD degree in a relevant STEM field (Data Science, Computer Science, Engineering, Mathematics, Physics, etc.)
  • 6+ years of experience working in data science, data engineering, software engineering, or MLOps
  • 6+ years of experience in AI/ML algorithm development workflow and data analysis in the major data modalities from NLP, time-series analysis, computer vision to graph models
  • 6+ years of experience in core programming languages and data science packages (Python, Keras, PyTorch, Pandas, Scikit-learn, Docker, Kubernetes, etc.)
  • 6+ years of experience with traditional ML and deep learning techniques (CNNs, RNN...

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