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Oracle Data Science Jobs in Indiana (NOW HIRING)

Inteliblue LLC

GIS Coordinator

Indianapolis, IN · On-site

... and other data science packages including web automation and scraping capabilities * Work with JavaScript and ArcGIS JavaScript API * Knowledge of SQL within Oracle and SQL Server platforms

Turing IT Labs

GIS Coordinator

Indianapolis, IN · On-site

... other data science packages including web automation and scraping capabilities Work with JavaScript and ArcGIS JavaScript API Knowledge of SQL within Oracle and SQL Server platforms Managerial ...

InfoLogitech, Inc.

GIS Coordinator

Indianapolis, IN · On-site

... data science packages including web automation and scraping capabilities Required 2 Years * Work with JavaScript and ArcGIS JavaScript API Required 2 Years * Knowledge of SQL within Oracle and SQL ...

OPENLANE

BI Engineer

Carmel, IN

$51 - $66.25/hr

Apply data science fundamentals to build predictive models and trend analyses * Develop scalable ... Advanced SQL skills and experience with relational databases (e.g., Snowflake, Redshift, Oracle ...

Brotherhood Mutual

Data Engineer II

Fort Wayne, IN

$113K - $135K/yr

Associate's degree in Information Technology, Computer Science, or a related field, or equivalent ... Oracle, Microsoft Fabric, AWS or similar) is required. * Bachelor's degree in Information ...

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Oracle Data Science information

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How much do oracle data science jobs pay per hour?

As of Jun 29, 2026, the average hourly pay for oracle data science in Indiana is $54.23, according to ZipRecruiter salary data. Most workers in this role earn between $46.44 and $63.12 per hour, depending on experience, location, and employer.

What are some common challenges Oracle Data Science professionals face when integrating machine learning models with enterprise databases?

Oracle Data Science professionals often encounter challenges related to data compatibility, scalability, and security when integrating machine learning models with enterprise databases. Ensuring that large, complex datasets are properly pre-processed and that models are efficiently deployed within Oracle's ecosystem can require close collaboration with database administrators and IT teams. Additionally, maintaining data privacy and compliance with organizational standards often requires careful planning and ongoing monitoring. Having a strong understanding of Oracle Cloud Infrastructure and its machine learning tools can greatly ease this integration process.

Is Oracle data science certification worth IT?

Oracle Data Science certification can enhance a data scientist's credentials by validating skills in machine learning, data analysis, and using Oracle tools. It may improve job prospects and salary potential, especially for roles involving Oracle cloud services and data platforms. However, its value depends on the job market and the candidate's experience and other skills.

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

AspectOracle Data ScienceData Analyst
Required SkillsData modeling, machine learning, SQL, Python, RData interpretation, Excel, SQL, visualization tools
Work EnvironmentTech companies, data science teams, cloud platformsBusiness units, reporting teams, analytics departments
CertificationsOracle certifications, data science certificationsNone specific, often Excel or business analytics certifications

Oracle Data Science roles focus on developing machine learning models and advanced analytics using Oracle tools and cloud platforms. Data Analysts primarily interpret data, create reports, and support decision-making with visualization and basic analytics. While both roles require SQL and data handling skills, Oracle Data Science positions demand expertise in machine learning and programming, whereas Data Analysts focus on data reporting and business insights.

Is 40 too late for data science?

Age is not a barrier to becoming an Oracle Data Science professional. Many data scientists start or transition into the field later in life, and skills such as programming, statistics, and machine learning can be developed at any age through online courses and certifications. Employers value experience and problem-solving ability, making age less relevant than skills and knowledge.

What are the key skills and qualifications needed to thrive as an Oracle Data Science professional, and why are they important?

To thrive as an Oracle Data Science professional, you need expertise in statistical analysis, machine learning, data modeling, and typically a degree in computer science, statistics, or a related field. Familiarity with Oracle Cloud Infrastructure, Oracle Machine Learning tools, SQL, and relevant certifications such as Oracle Data Science Certification are highly valuable. Strong analytical thinking, problem-solving, and effective communication skills help you translate complex data insights into actionable business strategies. These skills ensure you can leverage Oracle's platforms to derive meaningful insights and drive data-informed decision-making for organizations.

What is the salary of Data Scientist in Oracle?

The salary of a Data Scientist at Oracle typically ranges from $90,000 to $140,000 annually, depending on experience, location, and skill set. Entry-level positions may start lower, while experienced professionals with expertise in machine learning and data analysis can earn higher salaries. Benefits often include health insurance, bonuses, and professional development opportunities.

What is an Oracle Data Scientist?

An Oracle Data Scientist is a professional who uses Oracle's suite of data science tools and platforms to analyze large datasets, build predictive models, and provide data-driven insights for organizations. They leverage Oracle Cloud Infrastructure, Oracle Machine Learning, and other Oracle technologies to process, visualize, and interpret data. Their role often involves collaborating with business stakeholders to solve complex problems, automate processes, and support decision-making using advanced analytics and machine learning techniques.

Is IT hard to get a job at Oracle?

Getting a job as an Oracle Data Science professional can be competitive and typically requires strong skills in data analysis, machine learning, and familiarity with Oracle tools and platforms. Candidates often need relevant experience, certifications, and a solid understanding of data science concepts to improve their chances of employment.
What are popular job titles related to Oracle Data Science jobs in Indiana? For Oracle Data Science jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Oracle Data Science jobs in Indiana look for? The top searched job categories for Oracle Data Science jobs in Indiana are:
Oracle Data Science jobs near you
Infographic showing various Oracle Data Science job openings in Indiana as of June 2026, with employment types broken down into 1% As Needed, 90% Full Time, 8% Part Time, and 1% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $112,806 per year, or $54.2 per hour.
AI Data Engineer - Senior Consultant

AI Data Engineer - Senior Consultant

Deloitte

Indianapolis, IN • Hybrid

$99K - $137K/yr

Other

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

Deloitte rating

8.0

Company rating: 8.0 out of 10

Based on 89 frontline employees who took The Breakroom Quiz

55th of 139 rated financial services

Job description

AI Engineer Senior Consultant

Our Deloitte Human Capital team transforms technology platforms, drives innovation, and helps make a significant impact on our clients' success. We are hiring an AI Engineer to build and operate the data, features, and GenAI foundations that power Human Capital AI products and analytics. You will work with an AI Data Engineer (data ingestion, curation, governance, platform foundations) and a Lead AI Solutions Architect (end-to-end solution architecture, integration patterns, non-functional requirements), partnering closely with product, data science/ML, security, and platform engineering to deliver reliable, secure, and scalable AI solutions.

This role is hands-on and delivery-oriented: you will ship production pipelines and services that support model training, real-time inference, and LLM applications using Claude-, GPT/Codex-, and Gemini-class models, and more implemented with strong governance, observability, and cost/performance discipline.

Recruiting for this role ends on August 30, 2026

Work You'll Do:

As an AI Engineer Senior Consultant, you will design, build, and run the trusted, governed data + feature + retrieval layer used by AI/ML and GenAI solutions. You will deliver reproducible datasets and features, operationalize quality and lineage, and enable secure consumption patterns for both predictive ML and LLM-based experiences.

Key Responsibilities:

  • Partner with the Lead AI Solutions Architect and AI Data Engineer to translate Human Capital product needs into secure, scalable technical designs and delivered solutions (APIs, services, pipelines, containers/serverless) meeting availability, performance, and security expectations.
  • Build and operationalize LLM-enabled capabilities (e.g., copilots, HR knowledge assistants, summarization, policy Q&A) using Claude/GPT(Codex)/Gemini, including secure endpoints, tool/function calling, and reusable prompt/context patterns.
  • Implement LLM application patterns including RAG, document ingestion/chunking, embeddings, vector/hybrid search, and retrieval/evaluation telemetry.
  • Deliver governed datasets and feature engineering/serving for ML training and real-time inference (online/offline consistency, caching, latency SLOs, backfills).
  • Implement safety, privacy, and access controls (PII handling, prompt-injection defenses, content filtering, policy-based access) with security and risk stakeholders.
  • Establish data/model reliability and cost-performance discipline (data quality, schema evolution, lineage/metadata, monitoring; right-sizing, query tuning, LLM token/cost telemetry).
  • Contribute to MLOps/LLMOps and production operations (versioning, reproducibility, CI/CD, automated testing, observability, incident response); support design reviews, deployment readiness, and runbooks.

The Team

HC Forward is a dedicated innovation partner accelerating the future of Human Capital by building market-aligned products, platforms, and services that apply AI, data, and engineering to modernize HR experiences and outcomes.

Required Qualifications:

  • Bachelor's degree in a STEM field (e.g., Computer Science, Engineering, Statistics, Data Science)
  • 4+ years building and delivering LLM/GenAI solutions with Claude/GPT(Codex)/Gemini-class models, including prompt/context design, tool/function calling, evaluation, and production integration.
  • 4+ years implementing RAG/retrieval (document processing, embeddings, vector/hybrid search) with enterprise governance controls.
  • 4+ years of modern data & AI engineering, including data modeling, batch/streaming pipelines, structured/unstructured processing, and feature engineering/serving fundamentals.
  • 4+ years building production, real-time inference services (API design, latency/performance, reliability patterns).
  • 4+ years leading platform/integration engineering across enterprise systems; strong API/integration experience (REST, GraphQL, event-driven, microservices, middleware).
  • 4+ years DevOps/DevSecOps experience (CI/CD, IaC such as Terraform/CloudFormation, Docker/Kubernetes, observability/monitoring).
  • 4+ years leading security/compliance efforts; familiarity with enterprise security controls (IAM, encryption, secrets, audit logging) and data/privacy (PII, retention, access controls); SOC 2/GDPR/HIPAA exposure a plus.
  • Ability to travel 0-25%, on average, based on client and project needs.
  • Limited immigration sponsorship may be available

Preferred Qualifications:

  • Advanced degree (MS/PhD) and/or relevant certifications (cloud and AI/ML).
  • 4+ years of experience with Human Capital platforms and integrations (e.g., Workday, SAP SuccessFactors, Oracle HCM, Salesforce) and HR data domains.
  • 4+ years of experience operationalizing LLMOps/MLOps capabilities (evaluation, monitoring, governance workflows, model/prompt/version management).
  • 4+ years of cloud experience on AWS/Azure/GCP (one or more), including managed data platforms and scalable compute patterns.
  • 4+ years of experience with structured problem solving, translating business needs into requirements, acceptance criteria, and shippable increments.
  • 4+ years of experience with stakeholder communication: ability to explain AI/GenAI trade-offs (quality vs. latency vs. cost vs. risk) and document decisions.
  • 4+ years of experience collaborating across product, data science/ML, data engineering, platform, and security.
  • 4+ years of experience with treat testing, monitoring, and operational readiness as core responsibilities.
  • 4+ years of experience with ethics and privacy awareness being able to recognize consent/PII/bias boundaries and escalate appropriately.

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 $113,100 to $208,300.

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.

Possible Locations: Atlanta, Austin, Baltimore, Boston, Charlotte, Chicago, Cincinnati, Cleveland, Columbus, Costa Mesa, Dallas, Denver, Detroit, Hartford, Houston, Indianapolis, Jacksonville, Kansas City, Las Vegas, Los Angeles, McLean, Miami, Milwaukee, Nashville, New Orleans, New York, Philadelphia, Pittsburgh, Portland, Raleigh, Richmond, Sacramento, San Antonio, San Diego, San Francisco, San Jose, Seattle, St. Louis, Stamford, Tampa, Tempe

Information for applicants with a need for accommodation: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-assistance-for-disabled-applicants.html

For more information about Human Capital, visit our landing page at: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-human-capital-consulting-jobs.html

#HCFY26 #IIOFY26

Qualifications:

AI Engineer Senior Consultant

Our Deloitte Human Capital team transforms technology platforms, drives innovation, and helps make a significant impact on our clients' success. We are hiring an AI Engineer to build and operate the data, features, and GenAI foundations that power Human Capital AI products and analytics. You will work with an AI Data Engineer (data ingestion, curation, governance, platform foundations) and a Lead AI Solutions Architect (end-to-end solution architecture, integration patterns, non-functional requirements), partnering closely with product, data science/ML, security, and platform engineering to deliver reliable, secure, and scalable AI solutions.

This role is hands-on and delivery-oriented: you will ship production pipelines and services that support model training, real-time inference, and LLM applications using Claude-, GPT/Codex-, and Gemini-class models, and more implemented with strong governance, observability, and cost/performance discipline.

Recruiting for this role ends on August 30, 2026

Work You'll Do:

As an AI Engineer Senior Consultant, you will design, build, and run the trusted, governed data + feature + retrieval layer used by AI/ML and GenAI solutions. You will deliver reproducible datasets and features, operationalize quality and lineage, and enable secure consumption patterns for both predictive ML and LLM-based experiences.

Key Responsibilities:

  • Partner with the Lead AI Solutions Architect and AI Data Engineer to translate Human Capital product needs into secure, scalable technical designs and delivered solutions (APIs, services, pipelines, containers/serverless) meeting availability, performance, and security expectations.
  • Build and operationalize LLM-enabled capabilities (e.g., copilots, HR knowledge assistants, summarization, policy Q&A) using Claude/GPT(Codex)/Gemini, including secure endpoints, tool/function calling, and reusable prompt/context patterns.
  • Implement LLM application patterns including RAG, document ingestion/chunking, embeddings, vector/hybrid search, and retrieval/evaluation telemetry.
  • Deliver governed datasets and feature engineering/serving for ML training and real-time inference (online/offline consistency, caching, latency SLOs, backfills).
  • Implement safety, privacy, and access controls (PII handling, prompt-injection defenses, content filtering, policy-based access) with security and risk stakeholders.
  • Establish data/model reliability and cost-performance discipline (data quality, schema evolution, lineage/metadata, monitoring; right-sizing, query tuning, LLM token/cost telemetry).
  • Contribute to MLOps/LLMOps and production operations (versioning, reproducibility, CI/CD, automated testing, observability, incident response); support design reviews, deployment readiness, and runbooks.

The Team

HC Forward is a dedicated innovation partner accelerating the future of Human Capital by building market-aligned products, platforms, and services that apply AI, data, and engineering to modernize HR experiences and outcomes.

Required Qualifications:

  • Bachelor's degree in a STEM field (e.g., Computer Science, Engineering, Statistics, Data Science)
  • 4+ years building and delivering LLM/GenAI solutions with Claude/GPT(Codex)/Gemini-class models, including prompt/context design, tool/function calling, evaluation, and production integration.
  • 4+ years implementing RAG/retrieval (document processing, embeddings, vector/hybrid search) with enterprise governance controls.
  • 4+ years of modern data & AI engineering, including data modeling, batch/streaming pipelines, structured/unstructured processing, and feature engineering/serving fundamentals.
  • 4+ years building production, real-time inference services (API design, latency/performance, reliability patterns).
  • 4+ years leading platform/integration engineering across enterprise systems; strong API/integration experience (REST, GraphQL, event-driven, microservices, middleware).
  • 4+ years DevOps/DevSecOps experience (CI/CD, IaC such as Terraform/CloudFormation, Docker/Kubernetes, observability/monitoring).
  • 4+ years leading security/compliance efforts; familiarity with enterprise security controls (IAM, encryption, secrets, audit logging) and data/privacy (PII, retention, access controls); SOC 2/GDPR/HIPAA exposure a plus.
  • Ability to travel 0-25%, on average, based on client and project needs.
  • Limited immigration sponsorship may be available

Preferred Qualifications:

  • Advanced degree (MS/PhD) and/or relevant certifications (cloud and AI/ML).
  • 4+ years of experience with Human Capital platforms and integrations (e.g., Workday, SAP SuccessFactors, Oracle HCM, Salesforce) and HR data domains.
  • 4+ years of experience operationalizing LLMOps/MLOps capabilities (evaluation, monitoring, governance workflows, model/prompt/version management).
  • 4+ years of cloud experience on AWS/Azure/GCP (one or more), including managed data platforms and scalable compute patterns.
  • 4+ years of experience with structured problem solving, translating business needs into requirements, acceptance criteria, and shippable increments.
  • 4+ years of experience with stakeholder communication: ability to explain AI/GenAI trade-offs (quality vs. latency vs. cost vs. risk) and document decisions.
  • 4+ years of experience collaborating across product, data science/ML, data engineering, platform, and security.
  • 4+ years of experience with treat testing, monitoring, and operational readiness as core responsibilities.
  • 4+ years of experience with ethics and privacy awareness being able to recognize consent/PII/bias boundaries and escalate appropriately.

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 $113,100 to $208,300.

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.

Possible Locations: Atlanta, Austin, Baltimore, Boston, Charlotte, Chicago, Cincinnati, Cleveland, Columbus, Costa Mesa, Dall...

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