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Data Science Engineer Jobs in Indiana (NOW HIRING)

Data Engineering is a key role in the development team and is responsible for building and ... Bachelor's degree in Computer Science, Applied Mathematics, Engineering, or any other technology ...

AI Data Engineer - Manager

Indianapolis, IN

$109K - $131K/yr

You will manage day-to-day delivery with an onshore/offshore team, partnering with data science, ML engineering, and product stakeholders to translate use cases into production-ready pipelines and ...

Data Systems/Solutions Engineer

Indianapolis, IN · On-site

$109K - $131K/yr

The position emphasizes the development of robust, secure, and reproducible data infrastructure that supports data science, analytics, and AI-driven research. The Engineer applies modern software ...

Data Engineer

Woodburn, IN · On-site

$102K - $123K/yr

Data Engineer Build a Career That Matters with One of the World's Most Respected Employers ... Minimum of 1 to 3 years of Computer Science, Management of Information Systems, Application ...

Data Engineer

Woodburn, IN · On-site

$102K - $123K/yr

Data Engineer Build a Career That Matters with One of the World's Most Respected Employers ... Minimum of 1 to 3 years of Computer Science, Management of Information Systems, Application ...

Computer Engineer IV

Crane, IN

$111K - $131K/yr

Support data science efforts through visualization and analytics tools * Develop and maintain dashboards using tools such as Qlik * Collaborate with data engineers, systems engineers, and developers ...

Senior AI/ML Engineer

Bedford, IN · On-site

$93K - $128K/yr

... data science. * Expertise in developing, deploying, and securing AI/ML applications within mission-critical or defense environments. * Demonstrated experience with LLMs, MLOps pipelines, and modern ...

Degree in Analytics, Statistics, Mathematics, Computer/Data Science, Engineering, or a related field. 6+ years of experience in data analytics, data science, or related fields. 3+ years in customer ...

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Showing results 1-20

Data Science Engineer information

See Indiana salary details

$42.3K

$123.4K

$168.9K

How much do data science engineer jobs pay per year?

As of Jun 21, 2026, the average yearly pay for data science engineer in Indiana is $123,433.00, according to ZipRecruiter salary data. Most workers in this role earn between $109,000.00 and $130,800.00 per year, depending on experience, location, and employer.

Is AI replacing data scientists?

AI is transforming the role of data science engineers by automating routine tasks and enabling more advanced analysis, but it does not replace the need for skilled professionals who interpret data, develop models, and ensure ethical use. Data scientists and data science engineers are increasingly working alongside AI tools to enhance decision-making and innovation. The demand for expertise in programming, statistical analysis, and machine learning remains strong in the industry.

What are the key skills and qualifications needed to thrive in the Data Science Engineer position, and why are they important?

A Data Science Engineer should have a strong background in statistics, machine learning, programming (typically Python or R), and data engineering, often supported by a degree in computer science, engineering, or a related field. Familiarity with data processing frameworks (like Spark or Hadoop), cloud platforms (AWS, GCP, or Azure), and certifications in data science or cloud technology are highly valued. Excellent problem-solving skills, communication abilities, and collaboration are essential soft skills for working effectively in cross-functional teams. These competencies enable Data Science Engineers to build scalable data solutions, deliver actionable insights, and drive business impact.

What are the typical daily responsibilities of a Data Science Engineer?

Data Science Engineers typically spend their days designing and building data pipelines, preparing and cleaning large datasets, and developing machine learning models to solve business problems. They work closely with data scientists, software engineers, and business stakeholders to translate requirements into scalable technical solutions. Responsibilities also include deploying models to production, monitoring their performance, and iterating on solutions based on feedback. This role offers a dynamic mix of coding, data analysis, and teamwork, making each day varied and intellectually engaging.

Is 40 too late for data science?

Data Science Engineers can enter the field at any age, as success depends on skills, experience, and continuous learning. Many professionals transition into data science later in their careers by acquiring relevant knowledge in programming, statistics, and tools like Python or R. Age is less important than demonstrated expertise and the ability to adapt to evolving technologies.

What is the 80 20 rule in data science?

The 80/20 rule in data science suggests that roughly 80% of the results come from 20% of the efforts or features. Data scientists often use this principle to focus on the most impactful variables, optimize models, and prioritize tasks for efficiency.

What is a Data Science Engineer job?

A Data Science Engineer is a professional who bridges the gap between data science and software engineering. They focus on designing, building, and maintaining scalable data pipelines, infrastructure, and machine learning models for production use. Their role involves data preprocessing, model deployment, performance optimization, and integrating AI solutions into applications. They work closely with data scientists, software engineers, and DevOps teams to ensure efficient data workflows.

What does a data science engineer do?

A data science engineer designs, develops, and maintains data pipelines and infrastructure to support data analysis and machine learning models. They work with large datasets, use programming languages like Python or Scala, and often collaborate with data scientists and software engineers to implement scalable data solutions.
What are popular job titles related to Data Science Engineer jobs in Indiana? For Data Science Engineer jobs in Indiana, the most frequently searched job titles are:
Infographic showing various Data Science Engineer job openings in Indiana as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $123,433 per year, or $59.3 per hour.
AI Engineering Manager - SFL Scientific

AI Engineering Manager - SFL Scientific

Deloitte

Indianapolis, IN • On-site

Other

Posted yesterday


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 86 frontline employees who took The Breakroom Quiz

58th 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.
Are you passionate about leading the charge in emerging technologies? Do you want to join an award-winning team offering diverse opportunities, from account executives and data scientists to AI strategists, machine learning experts, and data engineers? If so, the AI Engineering Manager at SFL Scientific might be the perfect fit. SFL Scientific, a Deloitte Business, is part of our broader Strategy Offering within the Strategy & Transactions practice. Our specialized team brings together key capabilities to design integrated solutions that drive transformational change for our clients. Join us to expand your technical career through leadership, consulting, and becoming an industry leader in the AI engineering community.

Recruiting for this role ends on 8/31/2026.
Work You'll Do
As an AI Engineering Manager you will support the design, development, and deployment of novel AI applications across healthcare, life sciences, manufacturing, consumer, energy, and other sectors. You will lead client engagements and design and deliver architecture for complex AI and R&D type problems. AI Engineering Manager are responsible for developing design patterns, infrastructure, and engineering resources by understanding business and use case priorities, defining the data strategy, and leading application deployment to solve our clients' use cases. They work cross-functionally with data scientists, DevOps and data engineers, project managers, and industry experts to develop robust AI platforms and cloud solutions.
In our consultative approach, we are platform agnostic and committed to accelerating the development of innovative AI solutions for our clients with the best possible tools; this spans all relevant technologies from on-prem and cloud deployment, high performance computing, automation, DevOps, LLM/MLOps, data engineering while streamlining IT and infrastructure. Key responsibilities include but are not limited to:

  • Work with clients to design, develop, and deploy new architectures to support machine learning & automation applications
  • Leverage advanced technical skills in modern data architecture, data science engineering, data transformation, and management of structured and unstructured data sources using cloud computing or on-prem technologies
  • Design and lead development on scalable, high-performance data architecture solutions that supports both the client business as well as AI/GenAI use cases
  • Support and enhance data architecture, and data pipelines, and define database schemas (Graph, SQL, NoSQL) to develop algorithm scalability and deployment based on agile business priorities and initiatives
  • Participate in architectural and deployment discussions to ensure solutions are designed for successful scale, security, and high availability in the cloud or on prem
  • Adopt best engineering practices in automation, HPC and AI/GenAI infrastructure and design patterns
  • Define and lead technology proof of concepts to ensure feasibility of new data and cloud technology solutions
  • Display strong thought leadership and execution in pursuit of modern data architecture principles and technology modernization
  • Mentor, motivate, and coach junior members on technical best practices and inspire professional development

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. 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:

  • Bachelor's degree in a STEM field (Computer Science, Engineering, Physics, etc.)
  • 6+ years of experience working in data engineering, data science, software engineering, MLOps specializing in AI and Machine Learning deployment
  • 6+ years of experience in designing cloud solutions and supporting production projects, including hands-on experience with AWS services (or Azure, GCP equivalents)
  • 6+ years of programming experience with Linux Shell/CLI, Python, SQL, PowerShell, etc.
  • 4+ years of experience managing teams in technical delivery and delivering complex and critical projects
  • 4+ years of experience in DevOps and leveraging CI/CD services: Puppet, Ansible, Chef, Airflow, Terraform, Jenkins etc.
  • 4+ years of experience with database development and ETL/ELT pipelines (relational, NoSQL, Neo4j)
  • 3+ years of experience with deployment and optimization: Kubernetes, Docker, NVIDIA TensorRT/Triton, RAPIDs, Kubeflow, MLflow, Kafka, etc.
  • 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:

  • Master's degree in Computer Science, Engineering, Physics, etc. or related STEM field
  • AWS/Azure Certifications (AWS/Azure Certified: SysOps Administrator, DevOps Engineer, Solutions Architect)
  • 2+ years of experience with GPU computing (CUDA, OpenCL) and HPC system software stack

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.
Are you passionate about leading the charge in emerging technologies? Do you want to join an award-winning team offering diverse opportunities, from account executives and data scientists to AI strategists, machine learning experts, and data engineers? If so, the AI Engineering Manager at SFL Scientific might be the perfect fit. SFL Scientific, a Deloitte Business, is part of our broader Strategy Offering within the Strategy & Transactions practice. Our specialized team brings together key capabilities to design integrated solutions that drive transformational change for our clients. Join us to expand your technical career through leadership, consulting, and becoming an industry leader in the AI engineering community.

Recruiting for this role ends on 8/31/2026.
Work You'll Do
As an AI Engineering Manager you will support the design, development, and deployment of novel AI applications across healthcare, life sciences, manufacturing, consumer, energy, and other sectors. You will lead client engagements and design and deliver architecture for complex AI and R&D type problems. AI Engineering Manager are responsible for developing design patterns, infrastructure, and engineering resources by understanding business and use case priorities, defining the data strategy, and leading application deployment to solve our clients' use cases. They work cross-functionally with data scientists, DevOps and data engineers, project managers, and industry experts to develop robust AI platforms and cloud solutions.
In our consultative approach, we are platform agnostic and committed to accelerating the development of innovative AI solutions for our clients with the best possible tools; this spans all relevant technologies from on-prem and cloud deployment, high performance computing, automation, DevOps, LLM/MLOps, data engineering while streamlining IT and infrastructure. Key responsibilities include but are not limited to:

  • Work with clients to design, develop, and deploy new architectures to support machine learning & automation applications
  • Leverage advanced technical skills in modern data architecture, data science engineering, data transformation, and management of structured and unstructured data sources using cloud computing or on-prem technologies
  • Design and lead development on scalable, high-performance data architecture solutions that supports both the client business as well as AI/GenAI use cases
  • Support and enhance data architecture, and data pipelines, and define database schemas (Graph, SQL, NoSQL) to develop algorithm scalability and deployment based on agile business priorities and initiatives
  • Participate in architectural and deployment discussions to ensure solutions are designed for successful scale, security, and high availability in the cloud or on prem
  • Adopt best engineering practices in automation, HPC and AI/GenAI infrastructure and design patterns
  • Define and lead technology proof of concepts to ensure feasibility of new data and cloud technology solutions
  • Display strong thought leadership and execution in pursuit of modern data architecture principles and technology modernization
  • Mentor, motivate, and coach junior members on technical best practices and inspire professional development

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. 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:

  • Bachelor's degree in a STEM field (Computer Science, Engineering, Physics, etc.)
  • 6+ years of experience working in data engineering, data science, software engineering, MLOps specializing in AI and Machine Learning deployment
  • 6+ years of experience in designing cloud solutions and supporting production projects, including hands-on experience with AWS services (or Azure, GCP equivalents)
  • 6+ years of programming experience with Linux Shell/CLI, Python, SQL, PowerShell, etc.
  • 4+ years of experience managing teams in technical delivery and delivering complex and critical projects
  • 4+ years of experience in DevOps and leveraging CI/CD services: Puppet, Ansible, Chef, Airflow, Terraform, Jenkins etc.
  • 4+ years of experience with database development and ETL/ELT pipelines (relational, NoSQL, Neo4j)
  • 3+ years of experience with deployment and optimization: Kubernetes, Docker, NVIDIA TensorRT/Triton, RAPIDs, Kubeflow, MLfl...

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