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Model Validation Remote Jobs in Indiana (NOW HIRING)

Relativity

Principal Applied Scientist

Indianapolis, IN · On-site +1

Posting Type Remote/Hybrid Job Overview WHO WE ARE Relativity is a leading legal data intelligence ... Validate model behavior rigorously using evidence, metrics, and experimentation, remaining open to ...

CSAA

$39.75 - $54.75/hr

... model, conceptual data models, SMART requirements) * Translate business requirements into ... Prepare business validation (UAT) plan. * Plans, manages and may complete testing of application ...

Presence

Indiana (remote) - School psychologist

Marion, IN · Remote

$48 - $51/hr

... valid state licenses or equivalent school psychologist certification * Active DOE licensure * 1 ... Evaluations will be compensated on a component billing model that is separate from the hourly rate

Belden

Data Technical Specialist - Remote

Richmond, IN · On-site +1

$104.90K - $155.10K/yr

The ideal candidate will have a strong background in SAP data models and migration processes ... Develop and implement data migration plans, including data cleansing, validation, and ...

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Model Validation Remote information

What are the key skills and qualifications needed to thrive as a Model Validation Remote, and why are they important?

To thrive as a Model Validation Remote, you need a strong background in quantitative disciplines such as mathematics, statistics, or finance, typically supported by a relevant degree. Proficiency with statistical software (like SAS, R, or Python), model risk management frameworks, and familiarity with regulatory guidelines (such as SR 11-7) are commonly required. Analytical thinking, attention to detail, and strong written communication are crucial soft skills in this role. These skills ensure accurate model assessments, regulatory compliance, and effective communication of complex findings to stakeholders.

What are some common challenges faced by professionals in remote model validation roles, and how can they be addressed?

Remote model validation professionals often encounter challenges such as maintaining clear communication with model developers and stakeholders, accessing secure data environments, and staying updated with evolving regulatory standards. To address these, it's important to leverage robust collaboration tools, schedule regular check-ins with cross-functional teams, and participate in ongoing training or knowledge-sharing sessions. Establishing clear documentation protocols and ensuring secure remote access to necessary data can also help maintain productivity and compliance.

What is model validation in a remote job context?

Model validation, especially in a remote setting, involves evaluating and verifying the accuracy, performance, and reliability of statistical or machine learning models from a location outside of a traditional office. Professionals in this role typically assess whether models meet regulatory requirements, function as intended, and are free from biases or errors. Remote model validators use various tools and techniques to conduct tests, write reports, and communicate findings with stakeholders via digital platforms. This work is essential in sectors like finance, insurance, and tech, where robust models drive critical decisions. Successful remote model validation requires strong analytical skills, clear communication, and proficiency with data analysis tools.

What is the difference between Model Validation Remote vs Model Validation on-site?

AspectModel Validation RemoteModel Validation on-site
Work EnvironmentRemote, home-basedOn-site, office or client location
Required CredentialsSimilar certifications, e.g., CFA, FRM, or relatedSame as remote, often with additional in-person requirements
Industry UsageFinancial institutions, banks, asset managersSame industries, with in-person collaboration
Work FlexibilityHigh, flexible hours and locationLess flexible, fixed hours and location

Both remote and on-site model validation roles require similar credentials and industry knowledge. The main difference lies in the work environment and flexibility, with remote positions offering greater convenience and location independence, while on-site roles facilitate direct collaboration and immediate access to resources.

What are popular job titles related to Model Validation Remote jobs in Indiana? For Model Validation Remote jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Model Validation Remote jobs in Indiana look for? The top searched job categories for Model Validation Remote jobs in Indiana are:
What cities in Indiana are hiring for Model Validation Remote jobs? Cities in Indiana with the most Model Validation Remote job openings:
Model Validation Remote jobs near you
Principal Applied Scientist

Principal Applied Scientist

Relativity

Indianapolis, IN • On-site, Remote

Other

Medical, Retirement

Posted 17 days ago

Job description

Posting Type

Remote/Hybrid

Job Overview

WHO WE ARE
Relativity is a leading legal data intelligence company building technology that helps users organize data, discover the truth, and act on it with confidence. Our AI-powered, cloud platform, RelativityOne, transforms massive volumes of complex information into actionable insights for litigation, investigations, regulatory inquiries, data breach responses, and other highstakes legal work where accuracy, trust, and defensibility are essential.
Relativity aiR is redefining document review through agentic AI systems that reason, cite their decisions, and scale across millions of documents. These systems automate complex legal workflows while keeping humans in the loop, enabling legal professionals to focus on what matters most.
WHAT WE DO
At Relativity, we are building a worldclass Applied Science organization focused on pushing the boundaries of intelligent systems in one of the most demanding and consequential domains: the legal system.
Applied Science Team
The Applied Science team sits at the core of Relativity's AI development. We are responsible for designing, validating, and operating the intelligent systems behind Relativity aiR. Our work goes far beyond simple model integrations. We build agentic systems that reason over documents, validate decisions statistically, remain auditable and defensible, and operate reliably at massive scale. Trust, reliability, and responsibility are foundational to everything we build.
Our team values curiosity, experimentation, rigor, and collaboration. We move quickly, validate assumptions with evidence, and simplify aggressively to deliver systems that are safe, reliable, and impactful in production.

Job Description and Requirements

ABOUT THE ROLE

As a Principal Applied Scientist, Reliability, you will lead the design and validation of intelligent systems that customers can trust in highstakes legal workflows. You will operate endtoend: understanding the problem space, designing solutions, validating them statistically, and bringing them to production in partnership with engineering, product, and customerfacing teams.

This role is ideal for an experienced applied scientist who thrives at the intersection of modeling, experimentation, and realworld system reliability, and who is motivated by building AI systems that are not only powerful, but also defensible, interpretable, and safe by design.

WHAT YOU'LL DO

  • Write productionquality code that solves real customer problems and scales cleanly, with systems designed to be easy to ship, operate, and maintain
  • Collaborate closely with fellow Applied Scientists as well as Engineers, Product Managers, Designers, and Customers
  • Design and execute statistically sound experiments and automate them into reusable benchmarks and evaluation frameworks
  • Rapidly prototype AI and MLpowered solutions and mature them into reliable, scalable production models
  • Select the appropriate modeling approach for each problem, ranging from classical machine learning techniques to frontier large language models
  • Validate model behavior rigorously using evidence, metrics, and experimentation, remaining open to changing course when the data demands it
  • Contribute to building intelligent systems that reason, cite their decisions, and operate defensibly at scale
  • Help push the boundaries of agentic AI while ensuring systems remain auditable, reliable, and responsible

WHAT WE'RE LOOKING FOR

  • 8+ years of professional experience in applied science, machine learning, or a closely related field
  • Master's or Ph.D. in Computer Science, Statistics, Applied Mathematics, or a related quantitative discipline, or equivalent professional experience
  • Proven ability to move quickly from prototype to production, simplifying complex ideas into robust systems
  • Experience reading, validating, and applying research with a healthy level of skepticism
  • Experience across a wide range of modeling techniques, from classical machine learning to largescale generative models
  • Familiarity with modern MLOps tooling and practices, including containers, workflow orchestration, deployment patterns, telemetry, and experimentation systems
  • Strong Python programming skills and experience with common data and ML libraries such as numpy, PyTorch, scikitlearn, and PySpark
  • Strong communication skills, with the ability to explain complex technical concepts clearly to both technical and nontechnical audiences
  • Endtoend ownership mindset, with the ability to understand new problem spaces, design solutions, and bring them to market alongside engineering, product, and support partners
  • A collaborative, curious, and adaptable approach, with comfort leading, questioning assumptions, and learning from failure

WHY WE COULD BE A GREAT FIT

HighImpact Problems

  • Work on intelligent systems that operate in one of the most highstakes domains, where trust, reliability, and defensibility truly matter.

Agentic AI at Scale

  • Build and extend AI systems that reason across millions of documents, cite their decisions, and automate complex legal workflows.

Scientific Rigor and RealWorld Impact

  • Apply deep experimentation and statistical validation to systems that ship to real customers and influence real outcomes.

Leadership and Growth

  • Lead technically while continuously learning in a thoughtful, supportive, and intellectually rich Applied Science organization.

Collaborative Culture

  • Join a team that values kindness, curiosity, technical excellence, and shared ownership of outcomes.

Compensation and Benefits

  • Competitive compensation, health and retirement programs, discretionary time off (DTO), parental leave for primary and secondary caregivers, companywide breaks, wellness resources, and an equity program.

Relativity is committed to competitive, fair, and equitable compensation practices.

This position is eligible for total compensation which includes a competitive base salary, an annual performance bonus, and long-term incentives.

The expected salary range for this role is between following values:

$224,000 and $336,000

The final offered salary will be based on several factors, including but not limited to the candidate's depth of experience, skill set, qualifications, and internal pay equity. Hiring at the top end of the range would not be typical, to allow for future meaningful salary growth in this position.

Required Skills:

Algorithms, Data Analysis, Machine Learning (ML), Natural Language, Python (Programming Language), Reinforcement Learning, Researching, Scientific Writing, Statistical Models, Technical Leadership

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