Top Hybrid Data Analysis Jobs

The Equity Analyst will research and analyze industrial stocks, publish reports, maintain valuation models, and communicate with clients. Requires expertise in financial analysis and investment insights.

The Decision Scientist analyzes data for product optimization, develops reports and dashboards, runs A/B tests, and collaborates with product teams to utilize insights for strategic decision-making.

The Staff Decision Scientist will provide analytics solutions and insights to clients, mentor junior team members, and optimize client success.

The Analyst will support strategic development through data analysis, reporting, and market research while collaborating with various teams to drive business initiatives.

As a Senior Associate, you will analyze complex problems, mentor junior members, build client relationships, and enhance service delivery through technical knowledge.

The role involves applying data analytics to financial crime issues using SQL and Python, engaging with clients, and enhancing technical skills.

The role involves implementing financial models, optimizing software applications using C++ and Python, and enhancing analytics library performance in collaboration with various teams.

The Analyst supports strategic development by analyzing data, preparing reports, and conducting market analyses to drive business growth.

This role involves supporting water and biodiversity initiatives, conducting data analysis, collaborating on projects, and providing technical expertise to enhance sustainability efforts.

As a Compliance Analyst, you'll monitor compliance controls, analyze data, manage training oversight, and collaborate cross-functionally to enhance compliance programs.

The role involves analyzing data to identify fraud trends, collaborating with teams to mitigate risks, and providing insights. Candidates must possess strong analytical, communication skills, and adaptability in a fast-paced environment.

The Behavioral Insights Fraud Chargebacks Analyst analyzes data to identify fraud patterns, investigate risks in the Bitcoin domain, and collaborate across teams to enhance risk controls and improve fraud detection processes.

Drive data-driven decision-making by analyzing datasets, identifying trends, and collaborating with teams to improve products and user experience.