Senior Data Analyst - Contract

Position: Senior Data Analyst, Transplant Logistics - Contract

Reports to: Director of Data Analytics, Transplant Logistics

• Not open to C2C at this time *
• 100% Onsite in our Andover, MA Office *

ROLE BACKGROUND

Transplant Logistics is a recently created organization responsible for leading all aspects of TransMedics' transplant logistics, enabling the exponential growth of the National OCS Program (NOP). The team's comprehensive scope includes data analytics, network and topology design, capacity planning, product and program management, and the daily execution of air and ground transplant logistics operations, managed by a world-class central command center operating 24/7. Reporting directly to the Director of Data Analytics, the Sr. data Analyst will be responsible for mining, manipulating, and analyzing data from multiple internal and external sources, using analytical and statistical rigor to solve complex problems and drive actionable business decisions. This individual will design, build, and maintain automated reporting, dashboards, and ongoing analysis to enable data-driven decisions across the Transplant Logistics organization and with partner teams.

Working closely with the Product, Finance, Logistics, and Tech teams, this position provides the opportunity to influence one of the highest impact areas of TransMedics and organ Transplantation in the US and worldwide. The ideal candidate for this role is an innovative, highly motivated, and self-starter analyst, comfortable with ambiguity, with strong attention to detail, and experience with logistics and network topology.

ESSENTIAL TASK AND DUTIES INCLUDE:

• Mine, manipulate, and analyze data from multiple internal and external sources, reporting key actionable insights using statistical rigor to inform the larger organization of noteworthy

trends that impact the business.

• Develop metrics, and automated dashboards to give visibility into key measures of logistics performance and provide deep dive analyses on their movements.

• Partner with the Product, Finance, Logistics, Clinical, and Tech teams to gather requirements, create reporting and drive analytics projects that help solve complex logistics challenges.

• Constantly investigate and support implementation of new optimization, AI and ML techniques to provide tactical and strategic solutions to address the evolving Transplant Logistics needs.

• Support the ongoing design of the NOP logistics network topology, estimate resource needs, resource assignments, schedule optimization, and operational cost and efficiency improvements.

• Perform other TransMedics tasks and duties as required.

BACKGROUND AND QUALIFICATIONS:

• 5+ years of professional experience.

• Advanced SQL skills and experience in scripting for automation, Python preferred.

• Experience programming to process and analyze large and complex datasets.

• Experience building KPIs and developing ad-hoc and automated dashboards and reports.

• Experience with data visualization using Tableau and Power BI. other similar tools.

• Expert level Excel skills, including knowledge of Macros, Pivot Charts, and Statistical Modeling.

• Knowledge of statistical modeling, machine learning, Neural Network modeling, Forecasting, and Geospatial data processing.

• Experience in designing and executing A/B tests, setting and evaluating goals and targets.

• Experience leveraging data-driven insights to optimize business strategies and drive continuous improvement.

• Experience working directly with business stakeholders, being able to seamlessly navigate between data and business needs.

• Self-starter, driver, and out-of-the-box thinker with a strong attention to detail and comfortable with ambiguity.

• "Can do" attitude, willingness to roll up sleeves up with a drive to win.

• Ability to work independently with minimal supervision and collaborate with teammates and cross-functional colleagues.

• Strong business ethics.

EDUCATION:

• BS in computer science, engineering, economics, math, or related field.

• Master's degree in statistics, data science, or an equivalent quantitative field is highly valued.