Top Remote Senior Data Management Jobs in NYC, NY

Lead and motivate a team of six data engineers, managing project timelines and deliverables while collaborating with product management to define technical projects. Oversee the design and development of the data platform, mitigate risks, and promote a culture of growth and innovation.

As a Senior Manager in PwC Intelligence, you will lead teams to address complex business challenges, leverage statistical knowledge, and develop innovative solutions. You will support client engagements and contribute to service offerings by utilizing data analysis, machine learning, and software engineering practices, enhancing operations and client relationships.

The Data Engineering Manager will lead the development of core data pipelines, mentor junior engineers, collaborate across disciplines, and ensure user privacy. Responsibilities include task planning, recruitment, and maintaining technical accuracy in the team's work.

Lead the Machine Learning team at OpenX, developing ML products for ad marketplaces. Collaborate with cross-functional teams to set vision and strategy, guide product development, and foster a collaborative team culture.

As a Data Engineering and Analytics Manager at Spark Advisors, you will lead the data function, overseeing the development of a data warehouse, implementing data products, and mentoring your team. You'll work closely with various teams to ensure efficient data processing and provide insights through analytics infrastructures and dashboards.

The Senior Credit Manager / Senior Staff Data Scientist will analyze data to develop credit risk strategies for personal loans and collaborate with various teams to enhance lending strategies and monitor risk trends. The role focuses on building algorithmic risk strategies and leveraging data for informed decision-making.

The Associate Manager of Data Annotation at Qualtrics will lead a multi-lingual team to enhance data collection and annotation processes, supporting machine learning initiatives. Responsibilities include overseeing project scoping, managing the annotation workflow, ensuring process improvements, and collaborating with product managers and data scientists to deliver high-quality datasets.