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Junior Quantitative Trader Jobs in Indiana (NOW HIRING)

Data Scientist

Warsaw, IN · On-site

$60 - $80/hr

Mentor junior data scientists on technical execution, code quality, and career development; lead ... related quantitative field; Master's strongly preferred * 3-5 years of hands‑on data science ...

Junior Quantitative Trader information

See Indiana salary details

$7

$25

$45

How much do junior quantitative trader jobs pay per hour?

As of Sep 7, 2026, the average hourly pay for junior quantitative trader in Indiana is $25.65, according to ZipRecruiter salary data. Most workers in this role earn between $15.58 and $31.59 per hour, depending on experience, location, and employer.

What does a junior quantitative trader do?

A Junior Quantitative Trader assists in developing, testing, and implementing trading strategies using mathematical models and statistical analysis. They work with large data sets to identify patterns, assess risks, and make recommendations for buying or selling financial instruments. Typically, they collaborate with senior traders and researchers, use programming skills to automate trades, and monitor market trends to optimize trading performance. This role often serves as an entry point into the fast-paced world of quantitative finance.

What are the key skills and qualifications needed to thrive as a junior quantitative trader?

To thrive as a Junior Quantitative Trader, you need a strong background in mathematics, statistics, and programming, typically supported by a degree in a quantitative field such as finance, mathematics, or computer science. Familiarity with programming languages like Python, R, or C++, as well as experience with trading platforms and data analysis tools, is essential. Strong analytical thinking, attention to detail, and effective communication skills help you identify opportunities and collaborate with team members. These skills are crucial for developing and executing successful trading strategies in fast-paced, data-driven financial markets.

What are some common challenges faced by junior quantitative traders when transitioning from academia to a trading floor?

Junior Quantitative Traders often find that moving from academic environments to the fast-paced trading floor can be challenging due to the need for quick decision-making and managing real-time market pressures. Unlike academic projects, trading requires balancing theoretical knowledge with practical constraints, such as risk limits and execution speed. Additionally, juniors must quickly learn to communicate complex quantitative findings in a clear and concise manner to senior traders and other stakeholders, fostering effective teamwork in a high-stress, results-driven environment.

How hard is it to get a job as a junior quantitative trader?

Securing a junior quantitative trader position is competitive and typically requires a strong background in mathematics, programming, and finance, often with a degree in a quantitative field such as mathematics, physics, or engineering. Candidates usually need relevant skills in programming languages like Python or C++, experience with data analysis, and sometimes internships or certifications. The hiring process often involves technical interviews and assessments of problem-solving abilities.

What are the most commonly searched types of Quantitative Trader jobs in Indiana?

The most popular types of Quantitative Trader jobs in Indiana are:

What are popular job titles related to Junior Quantitative Trader jobs in Indiana?

For Junior Quantitative Trader jobs in Indiana, the most frequently searched job titles are:

What job categories do people searching Junior Quantitative Trader jobs in Indiana look for?

The top searched job categories for Junior Quantitative Trader jobs in Indiana are:

What cities in Indiana are hiring for Junior Quantitative Trader jobs?

Cities in Indiana with the most Junior Quantitative Trader job openings:

Infographic showing various Junior Quantitative Trader job openings in Indiana as of August 2026, with employment types broken down into 81% Full Time, 17% Part Time, and 2% Contract. Highlights an 75% Physical, 5% Hybrid, and 20% Remote job distribution, with an average salary of $53,353 per year, or $25.7 per hour.

Data Scientist

Samba

Warsaw, IN • On-site

$60 - $80/hr

Other

Re-posted 10 days ago


Key responsibilities

  • Own end-to-end delivery of significant data science projects, including problem scoping, approach design, and production deployment.

  • Build and maintain production-quality Python and PySpark code, implementing advanced ML and AI workflows such as entity resolution, probabilistic record linkage, and semantic similarity.

  • Collaborate with cross-functional teams to translate business requirements into technical solutions and mentor junior data scientists on technical execution and best practices.


Job description

Samba is a media intelligence company. We know what the world is watching, reading, and thinking about — in real time, at scale, across every screen. Our data exists with the consent of over a billion people, organized into the most complete picture of consumer attention ever built. The biggest brands in the world use that picture to make smarter decisions. We think it’s the most interesting data asset on the planet, because it’s the most culturally relevant.

As a mid-level Data Scientist at Samba in Warsaw, you will own end-to-end delivery of significant data science projects with minimal guidance. You are a reliable, autonomous contributor with deep expertise in at least one of Samba's core domains — measurement, or audience modelling — and the technical range to build production-ready solutions using modern ML and AI methodologies. You'll work closely with peers, product, and engineering, and play an active role in mentoring junior data scientists on the team.

What You'll Do:
  • Own end-to-end delivery of significant data science projects — from problem scoping and approach design through to production deployment
  • Make sound, independently-reasoned decisions on methodology, model selection, and evaluation; document them clearly in technical solution documents covering problem statement, approach, metrics, and timeline
  • Lead solution design for your own initiatives; break down complex epics into well-scoped user stories with clear acceptance criteria, adopting DataOps and MLOps best practices throughout — experiment tracking, pipeline orchestration, model monitoring, and reproducibility
  • Build production-quality Python and PySpark code on Databricks — well-tested, documented, and reusable — and implement advanced ML and AI-powered workflows including entity resolution, probabilistic record linkage, embedding-based matching, semantic similarity, and LLM-augmented pipelines
  • Develop and maintain reusable tools, libraries, and documentation that improve team efficiency and technical standards; conduct code reviews with constructive, specific feedback that raises the bar
  • Mentor junior data scientists on technical execution, code quality, and career development; lead internal talks or workshops on ML topics
  • Collaborate cross-functionally with product, engineering, and operations — translate business requirements into technical specifications, partner with data engineering on scalable pipeline design, and participate in cross-functional design reviews and working groups
Who You Are:
  • Bachelor's degree required in Statistics, Data Science, Computer Science, Mathematics or a related quantitative field; Master's strongly preferred
  • 3–5 years of hands‑on data science experience with demonstrated ability to own and deliver complex, multi-sprint projects independently
  • Advanced Python with production-quality code, testing, and documentation; strong SQL and PySpark for billion-row datasets
  • Databricks workflows, Delta Lake, and job orchestration; working knowledge of cloud platforms (AWS or GCP)
  • Solid command of core ML — regression, classification, clustering, model evaluation, and experimental design — applied to complex, high-volume data
  • Proficiency with MLOps practices: experiment tracking, pipeline orchestration (Airflow), and reproducible model deployment
  • Exposure to modern AI methodologies: RAG systems, LLM-augmented models, vector databases, and semantic search
  • Strong communicator — able to translate technical work into clear documentation, user stories, and cross-functional conversations
  • Demonstrated ability to mentor junior data scientists and contribute to team standards
Preferred skills:
  • Hands-on experience with knowledge graph construction, entity resolution, or semantic data modeling (RDF, OWL, SPARQL, or equivalent graph frameworks)
  • Familiarity with probabilistic record linkage, identity graph approaches, or embedding-based entity matching at scale
  • Experience with causal inference methods (A/B testing, synthetic control, uplift modeling)
  • Experience with deduplication, enrichment, or web-to-TV linkage problems
  • Background in media, ad tech, or measurement — TV viewership (ACR/STB data), digital audience modeling, cross-platform measurement (linear + CTV/OTT), or identity resolution in privacy-constrained environments
  • Familiarity with the measurement and identity vendor landscape (Nielsen, Comscore, LiveRamp, The Trade Desk)

180,000 zł - 330,000 zł a year

Samba is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We strive to empower connection with one another, reflect the communities we serve, and tackle meaningful projects that make a real impact.

Samba may collect personal information directly from you, as a job applicant, Samba may also receive personal information from third parties, for example, in connection with a background, employment or reference check, in accordance with the applicable law. For further details, please see Samba's Applicant Privacy Policy. For residents of the EU, Samba Inc. is the data controller.

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