Top Remote Data Science Jobs in Indianapolis, IN

Lead development and evaluation of AI products for medical professionals using large-scale datasets. Create product and client-facing analytics, influence data team strategy, and collaborate with product managers, analysts, and engineers to execute data projects from ingestion through analysis to recommendations.

As a Data Scientist at SentiLink, you'll develop fraud detection models using machine learning, engage in product development, and support analysis across teams. This role emphasizes hands-on technical work and end-to-end project ownership in a fast-paced environment.

Design and train LLMs and agentic systems for cybersecurity using RLHF/RLAIF and supervised fine-tuning. Build agent architectures, tooling, retrieval/memory, and evaluation pipelines with rigorous statistical benchmarking. Optimize prompts and inference, collaborate with engineers to productionize prototypes, and drive research on agent planning, safety, and reliability.

The Data Analyst will analyze extensive datasets to identify behavioral patterns, create analytics, and collaborate on data projects with product managers and developers.

As a Staff Data Scientist at SentiLink, you will develop fraud detection models, conduct analyses, collaborate across teams, and drive the development of financial risk products.

Lead end-to-end data science projects, develop machine learning models, collaborate with stakeholders, mentor team members, and communicate insights effectively.

Lead product analytics to inform strategy and optimize user experience: translate business questions into analysis, build reliable analytics infrastructure, run A/B tests and ML/statistical analyses, track funnels and cohorts, support 0-to-1 product launches, and communicate actionable insights to cross-functional teams.

Build and validate machine learning and statistical models on large structured and unstructured datasets. Apply data mining, distributed processing (Hadoop/Spark/Kafka), and visualization tools to generate insights and integrate model outputs into production systems to support business decisions in financial services.

Apply machine learning, computer vision, and advanced analytics to business and scientific problems. Build and visualize data-driven solutions, design data science applications, work with cloud and distributed data ecosystems, collaborate across global teams and partners, and deliver deployable ML products in agile teams.

The Principal Data Scientist will lead data analysis projects, collaborate with product management, assess business impacts, ensure data governance, and mentor junior analysts. Must leverage statistical techniques and machine learning to drive product strategy and business outcomes.

Founding Data Scientist for Procure-to-Pay working cross-functionally to build models, metrics, simple data pipelines, dashboards, and reports. Analyze complex datasets, produce actionable insights through data storytelling, and partner with leadership to turn business problems into data-driven solutions that impact operations and growth.

The Senior Data Scientist will analyze data to drive product strategy, optimize performance, and support product launches, collaborating with cross-functional teams.

Data Scientists at BlueLabs build predictive models, collaborate on analytics products, and tackle complex data challenges while ensuring high data quality.

Drive analytics and modeling to inform product strategy for Property & Casualty insurance. Build and productionize ML/statistical models, create visualizations and dashboards, manage exposure tools and regulatory reporting, and partner with Actuarial, Underwriting, Distribution, and Legal to execute product initiatives.

As a Senior Data Scientist, you'll develop fraud detection models, perform detailed analyses, and work closely with teams to drive product innovation and business outcomes.

Lead strategy and execution for generative and multimodal vision systems, from research to production. Design model architectures, adaptation, evaluation, and deployment pipelines; improve realism, controllability, robustness, and temporal consistency; benchmark and guide model selection; mentor scientists and coordinate cross-functional engineering to ship production-ready AI capabilities.

Build, evaluate, and ship matching, recommendation, and ranking models for job-seeker experiences. Work with skills and occupation taxonomies and labor-market data, partner with Engineering to productionize and monitor models, and translate messy data into clear, actionable analysis for product and customers.

Design, build, and deploy predictive GTM models (LTV, attribution, propensity). Lead experimentation and causal analyses, define KPI measurement frameworks, partner with Data Engineering, and translate statistical insights into actionable recommendations for Sales, Marketing, and Customer Success.

Develop and tune ML models, productionize and deploy strategies for ML systems, and align cross-functionally to communicate performance metrics.

Embed within GTM Marketing to design experiments, build attribution, propensity, churn, segmentation, and conversion models; analyze product engagement and organic search signals; partner with analytics engineers to productionize models; and translate statistical results into actionable business recommendations.

Lead healthcare and pharmaceutical marketing analytics: analyze CRM, media, healthcare and behavioral data; build segmentation, attribution, audience scoring, and predictive models; develop measurement frameworks; use Python, SQL, BI and automation; translate insights for executives; mentor juniors and partner with Strategy, Media, and Client Services.

As a Data Scientist, you will build predictive models, develop software tools, and analyze geoscientific data to support mineral exploration and discovery.

The Data Scientist will develop predictive models, analyze geophysical data, and collaborate with geoscientists to enhance exploration programs, focusing on mineral deposits.

As a Data Scientist, you will develop predictive models, analyze geoscientific data, and collaborate with geoscientists to improve mineral exploration efforts.

Build and productionize AI/ML solutions on a modern AWS federal data platform: implement RAG/vector stores, develop and validate models and pipelines, automate via Airflow/Glue/Spark, integrate with ETL metadata, ensure security/compliance, write tests and documentation, and support agile delivery.