Top Entry Level Data & Analytics Jobs

Monitor prediction markets and perpetual futures by tracking news, trader sentiment, venues, volumes, open interest, funding rates, and market share. Research protocols and users, build dashboards and datasets, identify product opportunities for Pyth, size opportunities with market and on-chain data, and collaborate with product, engineering, and business development teams. Write research reports, present recommendations to leadership, and evaluate launched initiatives against their original theses.

Lead workforce analytics and planning for Neko Health’s US expansion. Build labor forecasts, staffing models, dashboards, and scheduling tools from scratch; analyze productivity, utilization, labor costs, absenteeism, overtime, and coverage. Apply AI and machine-learning methods to improve shift design, forecasting, and workforce efficiency. Partner with HR, Operations, and Medical Operations while supporting rota scheduling and shift coverage across multi-site clinics.

Collects and analyzes pit stop performance data across NASCAR, IndyCar, and sportscar programs. Responsibilities include filming and archiving practice footage, synchronizing video with timestamps, building analytical models, maintaining performance databases, and producing reports for coaches, engineers, and pit crews. The role requires advanced Excel, Microsoft Office, video analysis software, strong attention to detail, motorsports knowledge, and willingness to travel to racetracks and work weekends.

Build and maintain a governed analytics platform in Snowflake using dbt, including dimensional models, data transformations, tests, contracts, semantic layers, and migrated reporting. Integrate diverse operational sources, ensure data quality, document models, and collaborate through GitHub pull requests. Use AI coding tools responsibly while validating correctness, performance, and maintainability.

Build and maintain production data ingestion pipelines, transformation models, warehouses, and schemas for PerfectServe’s data platform. Deploy reliable, tested pipelines using idempotency and data-quality checks, apply dimensional and medallion modeling, participate in design reviews, and document owned pipelines and runbooks. The role requires SQL, programming experience, dbt or similar transformation tools, cloud data warehouse experience, ELT orchestration, AWS knowledge, and a strong data-testing mindset.

Provides GIS analysis, application development, geodatabase administration, mission-planning support, data processing, mapping, GPS and database support, and field collection system management at White Sands Missile Range. Maintains Army-compliant geospatial data, develops ArcGIS and ArcPad capabilities, supports plotters and supplies, and coordinates with Army and federal personnel to keep data layers current.

Develop and support BigQuery solutions for a large-scale Big Data project using Looker and Google Cloud Platform. Collaborate with experienced GCP engineers on a highly visible client project. The role is fully remote within the United States, with preference for West Coast candidates.

Supports end-to-end market research projects, including questionnaire and discussion guide development, data collection, quality control, analysis, visualization, reporting, and client-ready deliverables. Collaborates with internal teams and subcontractors while developing expertise in quantitative and qualitative research methodologies, software, and technology platforms. The role requires strong communication, analytical thinking, organization, attention to detail, and eagerness to learn.

Build and own customer-facing analyses, dashboards, and reusable reporting for ECP Insights. Conduct customer discovery, define reporting needs, write SQL and Python or PySpark in Databricks, contribute dbt models, validate accuracy, explain methodologies, and help prioritize the product roadmap. Collaborate with product, engineering, and customer-facing teams while handling HIPAA-protected health information.

Own Qualitate’s data engineering foundation by building pipelines for structured and unstructured data, designing relational and non-relational data models, and developing AI-powered enrichment workflows. Establish data quality monitoring, integrations, schemas, contracts, lineage, and documentation. Partner with Applied AI, Research, and Engineering while shaping the company’s early data architecture and enabling customer data integrations.