Top Data & Analytics Jobs

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.

Summer technology intern supporting data analytics solutions, including SQL and Python data extraction, transformation, pipelines, reports, and Tableau dashboards in Snowflake. The role applies AI/ML, predictive analytics, natural language querying, and GenAI-assisted analysis to business decision-making. Interns collaborate in Agile teams, refine development backlogs, learn emerging technologies, and build cross-functional relationships.

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.

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.

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.

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.

Lead client-facing CRM analytics and insights across segmentation, campaign measurement, predictive modeling, and AI-driven marketing. Translate goals into metrics and analytical plans, manage end-to-end delivery, ensure data pipeline integrity with engineering partners, and mentor junior analysts while driving scalable, repeatable analytics solutions and dashboards.

The Data & Analytics team at Surescripts transforms healthcare data into actionable insights, collaborating with various stakeholders to support critical decisions across the healthcare ecosystem.

Produce financial and market intelligence, build statistical and econometric models, develop dashboards and automated reports, perform A/B testing and ML-based forecasting, optimize programmatic ad campaigns, integrate third-party data, provide customized measurement products, and support client analyses and strategic planning.

Build and maintain BI dashboards and reports, partner with business teams to translate requirements into SQL datasets, ensure governed data and visualization standards, manage BI tool lifecycle, and apply advanced analytics to uncover insights from complex data.

Lead development, validation, and operationalization of P&C actuarial models and workflows. Convert actuarial requirements into production-ready code, leverage cloud/AI tools, validate data pipelines, produce client-ready reporting, and liaise between actuarial SMEs and engineering teams while contributing to practice tooling and business development.

Lead development of statistical and simulation-based models to evaluate alternative datasets, assess portfolio risk, and optimize private markets investment strategies. Integrate and clean large, imperfect datasets; produce proprietary research, client-ready insights, and presentations. Partner with engineering, data, and validation teams to deploy analytics, maintain applications, and support investment, marketing, and client-use cases while managing multiple projects and stakeholder relationships.

Lead design and build of a cloud-based big data analytics platform: implement analytics infrastructure, integrate streaming and batch data, develop distributed processing pipelines, manage predictive analytics models, and apply machine learning and Bayesian methods. Work involves Scala on OS X and AWS, Java and Clojure, Kafka/Samza, NoSQL, and following TDD, Agile, CI/CD practices.

Develop and optimize high-volume Teradata data warehouse applications: design/architect solutions, model data, write and tune SQL, use Python scripting; ML and Hadoop experience a plus.

Design and architect data solutions and large-scale Java/J2EE systems. Define extensibility, scalability, availability and security requirements. Document current and target state, gather functional and non-functional requirements, recommend process optimizations, and consider impacts of existing infrastructure and networks.

Design and deliver full lifecycle enterprise and big-data architectures, translate complex functional and technical requirements into detailed designs, lead presales and client presentations, perform advanced analytics and ML modeling (logistic/linear regression, random forest, neural networks, time series), define data requirements and analytical plans, and collaborate with cross-functional teams and stakeholders.

Design and implement Tableau BI solutions; work with Big Data stack (Hive, Pig, MapR, Spark); develop ETL (Datastage, Unix scripting); apply Scala/Python for machine learning; leverage AMEX domain expertise.

Analyze A/B experiments and large datasets to determine why experiments performed well or poorly. Communicate results to business partners, validate and improve data-driven decision processes, build key metrics and modeling reports, and collaborate with business and engineering stakeholders.

The Research Engineer will design and build evaluation systems to measure data quality for Firecrawl's web data extraction, creating metrics and benchmarks, and collaborating on model improvements.