Top Data & Analytics Jobs

The Analyst, Revenue Strategy supports the sales team with reporting, forecasting, RFP analysis, and competitive analysis. Responsibilities include delivering revenue trends, assisting in strategy planning, and building reporting tools to consolidate performance insights.

The Operations Support Agent reviews and processes documents for clients, ensuring accurate uploads to accounts. Responsibilities include data entry, updating client information, delivering quality work in a fast-paced environment, and collaborating with various departments.

The Data Privacy Analyst will ensure compliance with data privacy laws and regulations, develop and maintain data privacy policies, conduct Privacy Impact Assessments, maintain records of processing activities, oversee data asset inventories, and provide training on data privacy best practices. The role also involves responding to data privacy incidents and representing Data Governance in project work.

The role entails using data and technology to enhance marketing operations by generating insights. Responsibilities include data analysis using SQL and Python, building revenue optimization models, aligning marketing planning with corporate strategy, and defining KPIs for performance measurement.

As a Machine Learning Researcher at Citadel Securities, you will apply advanced machine learning and AI techniques to analyze datasets, back-test models, and document your findings. Your work will contribute to developing innovative trading strategies in a fast-paced environment.

The Senior Data Engineer will develop and implement data analysis methodologies, create documentation to support data ingestion into a Unified Data Platform, collaborate with cross-functional teams, facilitate risk management, and provide quality assurance through testing. This role also involves translating business requirements into technical specifications and gathering expectations from stakeholders.

The Director of Machine Learning Operations will lead the ML Ops team to develop, implement, and oversee machine learning strategies. Responsibilities include managing ML infrastructure, deploying models, ensuring performance and scalability, and collaborating with cross-functional teams to integrate ML solutions into the advertising technology platform.