Top Data & Analytics Jobs

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.

Analyze PB-scale trading, transactional, operational and customer data; build visualizations, ML models and experiments; translate findings into actionable recommendations for trading, operations, product and executives in a fast-paced environment.

Own and build the end-to-end data layer: extraction pipelines from messy supplier emails and PDFs, the unified data model, reliable observable pipelines, and ML-driven extraction evaluation. Drive extraction accuracy, data quality, lineage, monitoring, and automation to scale coverage and enable engineering and product to depend on the data layer.

The role involves conducting impactful research and teaching at the graduate and undergraduate levels in information systems and technology, focusing on analytics and AI applications.

The role involves designing and developing tools in Python for trading and risk management, maintaining data pipelines, and collaborating with teams to enhance trading strategies using advanced techniques.

The Forecasting Manager is responsible for demand forecasting accuracy, managing forecasts using machine learning, and training marketing & sales teams. Collaborates with top management to ensure forecast consistency and leads process optimization projects.

Partner with investment professionals to design, build, and maintain data pipelines, Azure SQL environments, dashboards, Streamlit and LLM-based analytics tools, and vendor integrations to improve investment decision-making, data governance, and reporting across multi-asset portfolios.

Lead fraud detection and mitigation for a conversational BNPL product. Define fraud typologies, own repayment and chargeback analytics, manage fraud KPIs, design operational policies, collaborate on ML models and decisioning workflows, and coordinate SARs and compliance reporting.

Lead fraud risk for a conversational lending product (SNPL): define first-party fraud typologies, analyze repayment and chargeback trends, own fraud KPIs, design automated/manual blocking policies, coordinate ML/rules with central Fraud and Data teams, and liaise with Compliance on SARs and loan abuse.

This role focuses on sourcing, due diligence, and portfolio support in the AI investment ecosystem. It requires strong networking and analytical skills, combined with a proactive entrepreneurial spirit.

Develop methods for optimizing AI applications, implement automated evaluation systems, and work with clients to adapt tools for various domains.

The role involves collaborating to develop and refine large language models and generative models, utilizing expertise in machine learning and NLP.

Lead payments analytics by building scalable reporting, causal inference and ML models, designing experiments, partnering with product/engineering/finance to optimize payment processing, reconciliation, and settlement, and translating results into executive recommendations to drive global payments improvements.

Develop predictive models using data science and machine learning, work with data preparation and cloud resources, and solve complex problems.

Lead a team of data scientists to enhance patient experiences through data insights, predictive modeling, and analytics for healthcare solutions.