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Entry Level Python Data Science Jobs in Indianapolis, IN

RR

Data Systems/Solutions Engineer

Indianapolis, IN · On-site

$109K - $131K/yr

... supports data science, analytics, and AI-driven research. The Engineer applies modern software ... SQL and at least one general-purpose programming language (e.g., Python) * Experience with CI/CD ...

Turing IT Labs

GIS Coordinator

Indianapolis, IN · On-site

... Python, ArcPy, 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 ...

Staffingine LLC

DWD - Data Analyst

Indianapolis, IN · On-site

Bachelor's degree in Statistics, Mathematics, Computer Science, Economics, or a related field. * Proficiency in data analysis tools such as SQL, Python, R, or Excel. * Experience with data ...

STI

Data Analyst

Indianapolis, IN · On-site

Bachelor's degree in Statistics, Mathematics, Computer Science, Economics, or a related field. Proficiency in data analysis tools such as SQL, Python, R, or Excel. Experience with data visualization ...

Vergence

ETL/Data Engineer

Indianapolis, IN · On-site

$107K - $129K/yr

You will partner closely with data architects, analytics engineers, data scientists, business ... Python for data engineering - pandas, PySpark, REST API integration, unit testing (pytest). • ...

Vergence

ETL/Data Engineer

Indianapolis, IN

$107K - $129K/yr

You will partner closely with data architects, analytics engineers, data scientists, business ... Python for data engineering -- pandas, PySpark, REST API integration, unit testing (pytest). • ...

Indianapolis Colts

Data Engineer

Indianapolis, IN · On-site

$109K - $131K/yr

QUALIFICATIONS • Bachelor's degree in Computer Science, Information Systems, or a related field ... SQL and Python. • Familiarity with Microsoft Azure and cloud-based data platforms. • ...

MISO

AI Engineer

Carmel, IN · On-site

$152K - $177K/yr

Collaborating with a multidisciplinary team of data scientists, data engineers, and software ... Strong programming skills in Python and R (including libraries like scikit-learn, PyTorch, or ...

OPENLANE

Revenue Operations Analyst

Carmel, IN · On-site

$70K - $95K/yr

Bachelor's degree in Business, Economics, Data Science, Finance or related field (Master ... Strong analytical and technical skills, including proficiency in SQL and Python for data querying ...

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Entry Level Python Data Science information

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How much do entry level python data science jobs pay per hour?

As of Jul 11, 2026, the average hourly pay for entry level python data science in Indianapolis, IN is $56.03, according to ZipRecruiter salary data. Most workers in this role earn between $46.20 and $63.65 per hour, depending on experience, location, and employer.

What are some common challenges faced by entry-level Python data scientists when starting out, and how can they be addressed?

Entry-level Python data scientists often encounter challenges such as managing large datasets, understanding the nuances of real-world data (like missing or inconsistent values), and effectively communicating technical findings to non-technical stakeholders. To address these challenges, it's helpful to develop strong data cleaning skills, practice using libraries like pandas and scikit-learn, and focus on improving data visualization and storytelling abilities. Additionally, seeking feedback from more experienced team members and participating in collaborative projects can accelerate learning and help overcome early hurdles.

What is an entry level Python data scientist?

An entry level Python data scientist is a professional who uses Python programming language to analyze, interpret, and visualize data, typically in the early stages of their data science career. They are responsible for collecting, cleaning, and preparing data, performing basic statistical analyses, and building simple machine learning models under supervision. These roles often require proficiency in Python libraries like pandas, NumPy, and scikit-learn, as well as good problem-solving skills. Entry level data scientists may work in industries such as finance, healthcare, marketing, or technology to help organizations make data-driven decisions.

What are the key skills and qualifications needed to thrive as an Entry Level Python Data Scientist, and why are they important?

To thrive as an Entry Level Python Data Scientist, you need a strong understanding of statistics, data analysis, and proficiency in Python programming, typically supported by a relevant degree or coursework. Familiarity with data science libraries (such as pandas, NumPy, and scikit-learn), data visualization tools, and basic SQL is commonly required. Analytical thinking, problem-solving, and effective communication help you interpret data and present findings clearly. These skills ensure you can extract meaningful insights from data, collaborate effectively, and contribute to data-driven decision-making.

What is the difference between Entry Level Python Data Science vs Entry Level Data Analyst?

AspectEntry Level Python Data ScienceEntry Level Data Analyst
Required SkillsPython, SQL, statistics, machine learning basicsExcel, SQL, data visualization, basic statistics
CertificationsPython programming, data science fundamentalsExcel certifications, basic data analysis courses
Work EnvironmentTech companies, startups, data-driven teamsBusiness departments, marketing, finance teams
Common UsageBuilding models, data cleaning, predictive analyticsReporting, data visualization, trend analysis

Entry Level Python Data Science roles focus on programming, machine learning, and predictive modeling, often requiring Python and statistical knowledge. Entry Level Data Analyst positions emphasize data reporting, visualization, and basic analysis using tools like Excel and SQL. Both roles are common in various industries, but Python Data Science roles typically involve more technical and coding skills, while Data Analyst roles focus on interpreting data for business insights.

What are the most commonly searched types of Python Data Science jobs in Indianapolis, IN? The most popular types of Python Data Science jobs in Indianapolis, IN are:
What are popular job titles related to Entry Level Python Data Science jobs in Indianapolis, IN? For Entry Level Python Data Science jobs in Indianapolis, IN, the most frequently searched job titles are:
What job categories do people searching Entry Level Python Data Science jobs in Indianapolis, IN look for? The top searched job categories for Entry Level Python Data Science jobs in Indianapolis, IN are:
Entry Level Python Data Science jobs near you
Data Systems/Solutions Engineer

Data Systems/Solutions Engineer

RR

Indianapolis, IN • On-site

$109K - $131K/yr

Full-time

Life, Retirement, PTO

Re-posted 6 days ago

Job description

Position Summary
The Data Systems / Solutions Engineer serves as a key technical contributor within the Regenstrief Data Services team, functioning as a full-stack DataOps/MLOps engineer supporting research and analytics initiatives. This role is responsible for designing, building, and maintaining scalable, reliable data systems and pipelines that enable high-quality data ingestion, transformation, storage, and analysis.
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 engineering and data engineering practices to ensure data assets are accessible, well-governed, and aligned with clinical and research requirements.
This position is a hybrid position with at least one (1) to two (2) days of onsite activity based on business needs. This position is located in downtown Indianapolis IN.
Essential Duties and Responsibilities
Data Systems Engineering and Operations:
  • Design, build, and maintain data platforms, pipelines, and services that support research, analytics, and AI/ML workloads.
  • Develop and maintain scalable data architectures using modern data warehouse/lakehouse patterns.
  • Ensure data systems are reliable, performant, and designed for long-term sustainability.
  • Implement and maintain ETL/ELT workflows, data validation, and quality monitoring processes.

DataOps / MLOps Enablement:
  • Implement CI/CD practices for data and ML workflows, including testing, version control, and environment promotion.
  • Support reproducible analytics and ML pipelines, including experiment tracking and model lifecycle considerations.
  • Apply best practices for monitoring, observability, and incident response across data systems.

Cloud, Security, and Governance
  • Design and maintain cloud-based data solutions using secure and scalable architectural patterns.
  • Apply data governance, access control, and auditing practices consistent with HIPAA-aligned research environments.
  • Ensure appropriate handling of sensitive data through de-identification, access management, and compliance controls.
  • Optimize performance and cost efficiency across compute and storage resources.

Clinical and Research Data Support
  • Work with clinical and research stakeholders to translate domain requirements into technical solutions.
  • Support integration and use of clinical and biomedical data standards (e.g., EHR data, HL7/FHIR, OMOP).
  • Produce well-documented data assets and technical specifications to support reuse and transparency.

Collaboration and Project Support
  • Collaborate with data engineers, researchers, analysts, and project managers to deliver high-quality solutions.
  • Contribute to project planning, estimation, and execution.
  • Serve as a technical resource to team members and stakeholders.
  • Document systems, workflows, and architectural decisions clearly and consistently.

Continuous Learning and Innovation
  • Maintain current knowledge of emerging tools, technologies, and best practices in data engineering and AI.
  • Leverage AI-assisted development tools responsibly to improve productivity and code quality.
  • Participate in continuous improvement efforts across systems, processes, and workflows.

Knowledge, Skills, and Abilities
Technical Knowledge:
  • Proficiency in modern data engineering concepts, including:
    • Data warehouse and lakehouse architectures
    • Dimensional modeling and data transformation patterns
    • SQL and at least one general-purpose programming language (e.g., Python)
  • Experience with CI/CD pipelines and automated testing for data and ML workflows
  • Familiarity with data quality frameworks, lineage tracking, and observability tools
  • Understanding of cloud platforms, identity and access management, and security best practices
  • Knowledge of clinical and biomedical data standards and research workflows preferred

Analytical and Problem-Solving Skills
  • Ability to analyze complex technical problems and implement effective solutions
  • Strong troubleshooting skills across data ingestion, transformation, and delivery layers
  • Ability to balance reliability, performance, and cost considerations

Communication and Collaboration
  • Strong written and verbal communication skills
  • Ability to document technical concepts clearly for both technical and non-technical audiences
  • Demonstrated ability to collaborate effectively in multidisciplinary teams

Education and Experience
  • Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field required; Master's degree preferred.
  • Minimum of three (3) years of professional experience in data engineering, systems engineering, or a related technical role.
  • Demonstrated experience in:
    • Data platform or data pipeline development
    • Cloud-based data system
    • SQL and programmatic data processing
    • DataOps or MLOps practices

Performance Expectations
  • Works independently within established guidelines and best practices.
  • Produces high-quality work with minimal supervision.
  • Demonstrates sound judgment and attention to detail.
  • Contributes to continuous improvement of tools, processes, and team effectiveness.

Physical Demands
  • Ability to work standard business hours with flexibility as needed.
  • Ability to sit or stand for extended periods.
  • Ability to operate a computer and standard office equipment.
  • Ability to lift and move materials up to 20 pounds as needed.
  • Ability to travel occasionally for meetings or training.

Work Environment
  • Hybrid office and research environment.
  • Fast-paced, deadline-driven setting.
  • Requires collaboration with internal teams and external partners.
  • Regular use of computers, communication tools, and office equipment.

BENEFITS OF WORKING HERE
  • Work with a variety of diverse professionals in the healthcare industry
  • Free parking
  • Paid holidays, vacation, and sick time
  • Group Life and Voluntary Term Life insurance
  • Long-term and Short-term Disability plans
  • Employee Assistance Program (EAP)
  • Flexible Spending Account (FSA)
  • 403b Retirement Plan with gracious employer contributions
  • Fitness program
  • Pet insurance
  • Qualified employer for loan forgiveness

Please note sponsorship and/or relocation are not available for this position.
REGENSTRIEF INSTITUTE REQUIRES ALL EMPLOYEES TO RECEIVE THE INFLUENZA VACCINATION ANNUALLY UNLESS APPROVED FOR EXEMPTION.
Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities
This employer is required to notify all applicants of their rights pursuant to federal employment laws.
For further information, please review the Know Your Rights notice from the Department of Labor.

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