Top Senior Level Data & Analytics Jobs

The Lead Analyst in Quality Control Analytical oversees testing of drug products and substances, leads investigations and method optimizations, reviews lab documentation, authors quality records, and supports method development and validation activities while ensuring compliance with cGMP regulations.

The Data Engineer Manager will lead a team responsible for developing and maintaining data infrastructure, manage data engineering projects, and ensure quality and security across systems. The role involves mentoring team members, collaborating with cross-functional teams, and making hands-on contributions to technical work.

As a Decision Scientist in the Risk department, you'll analyze credit risk exposure, develop machine learning models, and collaborate with various teams to improve risk metrics and credit strategies. Your responsibilities will include monitoring risk indicators and making data-informed decisions with a focus on balancing growth and minimized risk.

The Senior Data Science Engineer will develop data solutions, collaborate with teams, oversee algorithms for data analysis, and support junior engineers. Responsibilities include managing scalable data processing platforms and making informed decisions while contributing to business goals.

The Senior Data Scientist will oversee and guide projects within machine learning and data science, play a key role in technical research assistance, and contribute to challenging projects funded by NSF. They will utilize their expertise to support the technical team and ensure the success of interventions in digital wellness.

Lead the Analyst Relations and Public Relations strategies at Board, ensuring alignment with business goals. Manage relationships with industry analysts, refine AR strategies, and execute a global PR strategy while collaborating with internal teams to maintain consistent messaging.

As a Data Scientist II at Putnam, you will lead a team to solve analytical problems for clients in the pharmaceutical and biotechnology sectors. Responsibilities include managing analytical workstreams, coaching junior team members, and synthesizing analyses into actionable recommendations. You will work extensively with big data, statistical testing, machine learning, and data visualization tools.