Top Remote Analysis Reporting Jobs in Indianapolis, IN

Build and operate reliable data pipelines transforming flight test, simulation, and operational data into versioned, traceable ML training datasets. Responsibilities include ingestion, normalization, time alignment, validation, dataset lineage, anomaly mining, labeling workflows, deployment feedback loops, monitoring, and data coverage analysis. Collaborate with flight test and operations teams on instrumentation and data access. The role is on-site in Boston and requires production data engineering experience supporting machine learning pipelines.

Data Engineer II will modernize BlueLabs’ data platform by leading Kimball dimensional modeling and legacy warehouse migrations, building reliable production data pipelines, and enforcing data quality standards. The role requires advanced SQL, Python, and dbt expertise, hands-on Snowflake and Redshift experience, and ownership of testing, documentation, observability, and scalable architecture. The engineer will collaborate cross-functionally, guide Data Engineer I team members, contribute to architectural decisions, and translate business logic into maintainable, cloud-agnostic data layers.

Design and implement end-to-end AI features, scalable data pipelines, ETL/ELT workflows, Generative AI and agentic systems, ML and BI solutions, and MLOps/LLMOps practices across AWS, Azure, and GCP. Apply RAG, embeddings, vector databases, security governance, evaluation, reliability, and guardrails. Own technical workstreams, mentor junior engineers, and promote software engineering best practices in consulting environments.

The Quantitative Researcher will manage yield opportunities, design algorithms, perform risk analysis, and collaborate with engineers on DeFi strategies.

Lead Databricks pre-sales discovery and design Lakehouse architectures, author proposal technical content, run proofs-of-concept, and act as lead architect on major engagements. Own the Databricks partner relationship and co-sell motion, drive certification and internal enablement, resolve performance and governance challenges, and ensure successful production handoffs while building partner-sourced pipeline and scaling the Databricks practice.

Build and maintain enterprise data platform and ETL/ELT pipelines, design and deploy data models, ensure data quality and governance, integrate third-party sources, and support analytics and AI initiatives across the organization.

Lead analytics for clinical decision support adoption and engagement: define metrics, query event-level usage, build dashboards, analyze funnels and cohorts, partner with product and cross-functional teams, and translate findings into actionable product recommendations to improve adoption and outcomes.

Build and own customer data ingestion and large-scale pipelines powering AI workers. Design syncing, retrieval, and data lake systems, improve reliability/observability, partner with product/backend teams, and contribute across infrastructure to give AI agents access to enriched customer data.

The role involves driving the identification of requirements, improving systems processes, developing prototypes, and ensuring usability in product development projects within an AI company.

Support supply chain and logistics by developing and automating reports and dashboards, analyzing large datasets to identify trends and process improvements, ensuring data accuracy, monitoring KPIs (on-time delivery, inventory turns, transportation costs), assisting root-cause analyses, and collaborating with operations, procurement, finance, and IT to deliver actionable insights.