Data Analyst

About the role

Remote position. Duration: 1 year with possible extensions. Open to supplement additional workload on the team.

Responsibilities

• Deliver defined data science, analytics, and digital work packages in support of Business Engineering & Strategy priorities, working with FTE project/business leads to understand requirements, milestones, and expected outputs.
• Lead end-to-end technical delivery and support of the DST business performance and operations dashboard portfolio in partnership with the Chief of Staff.
• Gather requirements and define, design, develop, and maintain dashboards covering budget, organizational goals, and other operations metrics, using platforms such as Tableau, Spotfire, Power BI, Databricks, Alteryx or comparable tools.
• Develop, test, document, and maintain data pipelines that ingest, transform, and deliver business and process data from approved enterprise and local sources.
• Develop first-pass analyses, prototypes, data mappings, visualizations, or other technical work products for review by project leads and SMEs; incorporate feedback into subsequent iterations.
• Troubleshoot and improve existing dashboards, data products, analytics workflows, and AI-enabled tools; deliver enhancements through iterative, customer-focused development.
• Translate defined business and technical requirements into solution designs, user stories, acceptance criteria, technical tasks, and deliverables.
• Perform manual workflow assessment or representative data analysis, when appropriate, to understand and validate a process before developing automation or scaled digital solutions.
• Support technical SME and stakeholder discussions by preparing analyses or prototypes, documenting relevant technical decisions and actions, and incorporating agreed feedback into the work product.
• Support cross-functional digital-transformation and continuous-improvement initiatives by providing data science, analytics, and technical expertise to FTE-led projects.

Requirements

• Bachelor's degree in Engineering, Operations, or Scientific discipline plus 2+ years of relevant professional experience.

Qualifications

• Data science, data analytics, or data engineering background strongly preferred, along with a basic understanding of Drug Substance business operations and/or bioprocessing.
• Experience applying data science, data engineering, analytics, AI-enabled solutions, or digital tools to bioprocessing analytics, business optimization, or operational decision-making.
• Experience using Python and/or SQL to prepare, transform, analyze, and derive insights from complex datasets; experience with Databricks or comparable data platforms is preferred.
• Experience developing reports, dashboards, and data visualizations using Tableau, Power BI, Spotfire, or comparable tools.
• Experience designing, developing, or supporting data pipelines, data models, and data-quality checks that enable reliable analytics, dashboards, and self-service reporting.
• Experience supporting process optimization, continuous improvement, or digital transformation initiatives through data analysis and technical solution development.
• Demonstrated ability to gather stakeholder requirements and translate them into defined technical requirements and practical, user-centered digital solutions.
• Strong written and verbal communication skills, including the ability to explain technical concepts, analyses, and recommendations to both technical and non-technical partners.
• Bachelor's degree in bioprocess engineering, chemical engineering, data science, computer science, or another quantitative discipline, plus relevant professional experience.

Skills

• Independently executes defined technical and analytical assignments with strong accountability, organization, and time management.
• Takes a hands-on approach to problem solving, including data exploration, analysis, troubleshooting, prototyping, and workflow testing.
• Comfortable working iteratively: develops a first-pass solution, seeks feedback, incorporates input, and refines the output.
• Applies sound judgment to solve problems independently, incorporates feedback constructively, and escalates barriers with clear context and proposed options.
• Collaborates effectively with technical SMEs, business partners, and project leads to understand requirements and deliver fit-for-purpose solutions.
• Demonstrates ability and willingness to rapidly learn unfamiliar business processes, data sources, digital platforms, and technical concepts.
• Brings curiosity and enthusiasm for applying digital solutions to biopharmaceutical operations.
• Maintains a high standard for data quality, documentation, accuracy, and attention to detail, including appropriate human review and validation of AI-assisted outputs.
• Communicates progress, findings, risks, and technical recommendations clearly and concisely.
• Demonstrates reliability and accountability for agreed deliverables and timelines.