Sr. Data Analyst

Thermo Fisher Scientific•Pittsburgh, PA

4d•Onsite

About The Position

Thermo Fisher Scientific Inc. is seeking a Sr. Data Analyst to lead strategic data science initiatives aimed at boosting revenue and market presence. This role involves leveraging data analytics and statistical methods to create insights and data-driven business solutions that enhance sales and marketing strategies. The analyst will formulate and execute data-driven strategies, convert complex datasets into actionable business insights, and develop advanced statistical models. Collaboration with cross-functional teams is key to identifying and solving business problems and seizing market growth opportunities. The position also includes analyzing and interpreting large datasets for strategic decision-making, executing A/B testing, curating product recommendations, and designing/maintaining database schemas. There will be collaboration on data science-driven web capabilities, digital technology projects, API development, AI-driven product development, and UX design. Agile methodologies (Scrum/Kanban) and Six Sigma for process improvement are to be implemented. Key performance indicators (KPIs) will be established and monitored, and a systemic program reporting structure will be designed. Continuous improvement will be driven by assessing program performance data. The role also involves enhancing and automating analytical tools and processes, contributing to sales engagement improvements, optimizing product strategy, and building outstanding digital campaign results. Up to 10% domestic and international travel may be required.

Requirements

Master’s degree or foreign degree equivalent in Data Analytics, Data Science, Digital Technology, Business Analytics, or a related field of study.
6 years of experience in marketing research, data analytics, or related experience.
Experiences in SQL, Python, Eloqua, Salesforce and Google Analytics & Six Sigma certification(Green Belt) are required.
Required knowledge or experience with: SQL Server; SPARK or Python; Visualization tools; Statistical analysis; Business analytics with data intelligence; Salesforce.com; Eloqua; Six Sigma certified; and Google Analytics qualified.

Responsibilities

Lead strategic data science initiatives to boost revenue and market presence.
Leverage data analytics and statistical methods to create insights and data-driven business solutions that enhance sales and marketing strategies.
Formulate and execute data-driven strategies to augment revenue.
Utilize analytical and statistical skills to convert complex datasets into actionable business insights.
Develop and implement advanced statistical models to drive sales and marketing effectiveness.
Collaborate with cross-functional teams to pinpoint and solve business problems and seizing opportunities for market growth.
Analyze and provide interpretations of large datasets for strategic decision-making and creating periodic and ad hoc reports.
Execute A/B testing to substantiate data science initiatives and optimize market strategies.
Curate and disseminate product recommendations through commercial and digital communication channels.
Design and maintain database schemas to support product features and ensure data integrity.
Optimize database performance through indexing, query optimization, and regular maintenance.
Collaborate with cross-functional team on data science driven web capability design and web performance analytics.
Work with corporate teams to conduct digital technology and data science driven API project and innovative AI-driven product development and UX design.
Implement Agile methodologies, including Scrum or Kanban, to manage project workflows and team collaboration.
Implemented performance evaluate approaches using Six Sigma methodology to improve processes, and enhance data management and digital tactics efficiency across the division.
Establish and monitor key performance indicators (KPIs) to gauge and steer program success.
Design and implement a systemic program reporting structure for use across the organization.
Assess program performance data to identify and advocate for continuous improvement.
Enhance, refine, and automate current analytical tools and processes for increased efficiency.
Coordinate with cross-functional teams, contributing to sales engagement improvements and product strategy optimizations.
Lead data science initiatives leading to optimized email campaign metrics and expanded collaboration with key suppliers.
Build and launch outstanding digital campaign results.