Top Data & Analytics Jobs

Own end-to-end analysis of payments, chargebacks, and user lifecycle to identify drivers of net loss. Deep-dive into fraud cases, design and evaluate A/B experiments and risk-rule changes, build monitoring dashboards, partner with Risk, Payments, and Product to convert insights into mitigations, and run ad-hoc analyses of emerging loss trends.

Lead strategy and delivery of enterprise streaming and social data products that serve as authoritative sources of truth. Ensure AI-ready, governed, semantically consistent data with metadata, lineage, observability, SLAs, and adoption plans. Partner with analytics, engineering, and commercial teams to define metrics, manage external data sources, enforce data contracts, and drive AI and predictive use cases for music consumption and audience insights.

Design, build, and maintain ETL/data pipelines and data models using Databricks and cloud platforms. Support BI (Power BI) reporting and ML workflows, apply SQL and analytical skills to enable data-driven insights.

Support analytics by cleaning, validating, and transforming data; build dashboards and KPI reports; perform trend, cohort, and A/B testing analyses; improve data pipelines and forecasting; present insights to cross-functional teams.

Summer internship performing data analysis, research, predictive modeling support, and reporting to generate business and risk-management insights. Communicate findings with visualizations, conduct market/peer research, and support financial, regulatory, and business intelligence needs across analytics teams including model risk, fraud, and portfolio management.

Lead strategy and execution to prevent, detect, and disrupt digital fraud, scams, and money mule activity. Build and mentor data science and analytics teams, develop ML predictive models, partner with product, cyber, vendors, and risk teams, and drive prevention-first controls, compliance, and operational efficiencies across payments, onboarding, and authentication channels.

Lead analytics partner to Community Support, driving data-driven roadmaps, scalable reporting and measurement, causal inference and experimentation, and improvements to agent/guest/host experiences via analytics, modeling, and stakeholder influence.

Support the Business Intelligence team with reporting, CRM (Salesforce) administration, data automation/integration, quantitative analysis, dashboards, and predictive/statistical modeling to inform ticket sales, marketing, and fan engagement.

Join a collaborative team to develop AI-driven equity trading signals using machine learning techniques on proprietary datasets.

Inceptive seeks candidates for research in biological software, collaborating with a multidisciplinary team to design accessible medicines and biotechnologies.

Lead enterprise analytics and data product strategy, defining an AI-enabled data marketplace, semantic models, governed self-service analytics, and tooling roadmaps. Partner with business and tech teams to translate needs into data products, shape AI-enabled capabilities, ensure trust and governance, drive adoption, and measure business value and quality.

Design and execute statistically rigorous analyses to quantify and inform safety and risk for autonomous driving systems. Apply Bayesian and frequentist methods (and ML where appropriate) to large, noisy or rare-event datasets, produce production-ready monitoring workflows, and communicate findings to engineers, safety stakeholders, and executives to support risk-based decision making.

As a Senior Impact Analyst, you will analyze sustainability challenges, design and manage interventions, and work closely with smallholder communities, emphasizing rigorous research and collaboration.

The Senior Data Scientist will design and deploy time-series forecasting models, collaborate with stakeholders, and operationalize models in cloud environments, focusing on demand planning across various industries.

Develop and execute quantitative models and analytical methods to assess credit risk for Single Family mortgage products (modification, short sale, foreclosure, distressed valuation). Independently design, implement, and validate predictive models, support business and risk decisions, perform data cleaning and processing, and collaborate with stakeholders to provide practical, innovative solutions.

As an Associate Engineer in Data Science, you will leverage data analysis and machine learning to solve complex problems and develop inspiring digital products.

Lead development and application of statistical and mathematical models to analyze complex datasets for DoD/IC clients. Work on classified networks, guide teammates, translate technical findings into visual and written products, and evaluate AI/ML system performance and robustness.

Develop econometric and statistical models to forecast asset price movements and macro variables, implement and validate algorithmic trading strategies, automate data processing in Python, monitor live trading automations and associated risk, and analyze macroeconomic releases and BLS datasets.

Entry-level Associate Data Analyst supporting analytics, data science, data engineering, and project management rotations. Deliver insights, build dashboards, automate reporting, partner with stakeholders, and apply ML/LLM tools to drive product and client analytics.

The Quantitative Researcher will develop and optimize trading strategies, analyze data for alpha signals, and collaborate on financial models.

Design, build, and maintain scalable data pipelines and platforms to ingest, merge, and prepare structured and unstructured data for analytics and AI. Lead multidisciplinary teams, perform data exploration and statistical analysis, and support use of LLMs/GenAI to enable mission-driven solutions across fraud detection, healthcare, and intelligence domains.

Design, build, and maintain scalable data pipelines, warehouses/lakes, and platforms. Lead multidisciplinary teams to implement ETL/ELT (batch and streaming), optimize data lake performance, enforce data governance, and support analytics and ML use cases on cloud and on-prem environments.

Early-career role analyzing PB-scale on-chain, transactional and customer data. Perform data engineering, ETL, querying, build visualizations and ML models, translate insights for teams, manage reporting environment, secure confidential data, and troubleshoot reports/databases.

Lead Aarden's publishable research: define research agenda, mine proprietary parcel and infrastructure data, run analyses using ML/AI tools, validate methodology with the data team, and publish insights (LinkedIn posts, white papers, media) that serve land-focused clients.

As a Machine Learning Engineer, you will enhance internal libraries for deep learning, collaborate with researchers, and optimize workflows for cost savings.