1

Research Python Jobs in Indianapolis, IN (NOW HIRING)

... scientists and researchers to interact with complex datasets intuitively and efficiently ... using Python (FastAPI, Flask, Django) or Node.js to support rich scientific workflows. • ...

... that enable scientists and researchers to interact with complex datasets intuitively and ... Design, develop, and support scalable full-stack applications and AI-powered solutions using Python ...

Data Systems/Solutions Engineer

Indianapolis, IN · On-site

$109K - $131K/yr

Design, build, and maintain data platforms, pipelines, and services that support research ... SQL and at least one general-purpose programming language (e.g., Python) * Experience with CI/CD ...

Showing results 21-40

Research Python information

See Indianapolis, IN salary details

$12

$56

$82

How much do research python jobs pay per hour?

As of Aug 8, 2026, the average hourly pay for research python 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.

Is Research Python good for research?

Research Python is a specialized role that involves using Python programming skills to support research activities, such as data analysis, automation, and modeling. Proficiency in Python, along with knowledge of scientific libraries like NumPy or pandas, makes it a valuable skill for research projects. The role often requires strong problem-solving abilities and familiarity with research environments or datasets.

What is a Research Python developer?

A Research Python Developer is a professional who uses the Python programming language to support and conduct research activities. They often work with data analysis, machine learning, simulation, and automation to solve scientific or academic problems. Their role may involve developing prototypes, processing large datasets, and collaborating with researchers to implement algorithms or models. Research Python Developers are commonly found in universities, research institutions, and tech companies focused on innovation.

What is the difference between Research Python vs Data Analyst?

AspectResearch PythonData Analyst
Required SkillsPython programming, research methodologies, data analysisData analysis, visualization, SQL, Excel
Work EnvironmentResearch labs, academic institutions, tech companiesBusiness settings, corporate offices, consulting firms
Common CertificationsPython certifications, research methodology coursesMicrosoft Excel, Tableau, SQL certifications
Industry UsageAcademic research, scientific projects, tech R&DBusiness intelligence, marketing, finance

Research Python focuses on using Python for scientific and academic research, emphasizing programming and research methodologies. Data Analysts primarily analyze and interpret data to support business decisions, often using tools like Excel and Tableau. While both roles require data skills, Research Python is more technical and research-oriented, whereas Data Analysts focus on data interpretation within business contexts.

Which research Python job is in demand?

Research Python roles in demand include data scientist, machine learning engineer, and AI researcher, often requiring strong programming skills, knowledge of libraries like NumPy and TensorFlow, and experience with data analysis. These positions are prevalent in industries such as technology, finance, and healthcare, with a focus on developing algorithms and models for data-driven insights.

What are the key skills and qualifications needed to thrive as a Research Python developer?

To thrive as a Research Python Developer, you need expertise in Python programming, data analysis, and a strong foundation in mathematics or computer science, often supported by an advanced degree. Familiarity with libraries such as NumPy, pandas, TensorFlow, and version control systems like Git is typically required. Analytical thinking, problem-solving, and effective communication are crucial soft skills for translating research goals into practical code. These skills are essential for developing robust research solutions, collaborating with interdisciplinary teams, and advancing scientific or technical projects.

What are some common challenges faced by Research Python developers when collaborating with cross-functional teams?

Research Python Developers often work alongside data scientists, domain experts, and engineers, which can present challenges such as aligning on project goals, translating research requirements into efficient code, and ensuring reproducibility of results. Effective communication and thorough documentation are key to overcoming these challenges. Additionally, Research Python Developers may need to adapt their code to integrate with different tools or platforms used by other team members, requiring flexibility and a willingness to learn new technical concepts.
What cities near Indianapolis, IN are hiring for Research Python jobs? Cities near Indianapolis, IN with the most Research Python job openings:
Infographic showing various Research Python job openings in Indianapolis, IN as of August 2026, with employment types broken down into 50% Full Time, and 50% Part Time. Highlights an 100% In-person job distribution, with an average salary of $116,551 per year, or $56 per hour.

Machine Learning Engineer

Bespoke Labs

Indianapolis, IN • On-site

Full-time

Re-posted 22 days ago


Job description

About Us

We are AI researchers and builders who understand how to curate data and RL environments that truly improve models. We curated OpenThoughts, one of the best open reasoning datasets, and have trained SOTA models such as Bespoke-MiniCheck and Bespoke-MiniChart.

We are embarked on a journey to build Environments that are entire digital worlds that can be used to push the frontier of agents.

What You'll Be Working On

You will work directly with our research team on RL environment and task creation for agent training. This means designing observation spaces, action spaces, reward signals, and success criteria for new environments — and building the infrastructure that makes world-scale RL training possible. This is a high-ownership role; you will be building novel systems, not maintaining legacy ones.

Must-Have Skills

3+ years of ML engineering experience — model training, fine-tuning, or post-training pipelines in research or production

Strong Python and deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed precision)

Hands-on experience with LLM post-training — SFT, RLHF, PPO, DPO, or reward model training — and understanding of how training data quality affects model behavior

Familiarity with RL frameworks (Gymnasium, dm_env) and the ability to design or modify reward functions for agent training objectives

Experience running experiments at scale on cloud or HPC (AWS, GCP, SLURM, or Ray)

Solid understanding of evaluation methodology — held-out sets, benchmark design, avoiding train/eval contamination