Commercial Real World Data Analyst II

Job Description As a Commercial Real World Data Analyst at Bristol Myers Squibb, you will have the opportunity to enable data-driven decision-making by translating complex business needs into scalable technical solutions. Your role will involve expertise in commercial pharmaceutical datasets, primarily in Oncology and Haematology, and proficiency in BI tools like Power BI, Tableau, and AWS-based data pipelines. You will be expected to conduct exploratory data analysis with minimal guidance and contribute to broader data strategy efforts, including brand planning, budget forecasting, and Statement of Work (SoW) management. Familiarity with GenAI tools to drive innovation is considered a plus. **Key Responsibilities:** - Develop and maintain dashboards and reports using tools such as Power BI and Tableau to support brand performance tracking, patient journey insights, and forecasting inputs. - Utilize SQL and Python skills, along with therapeutic area knowledge, to conduct exploratory analysis on pharma datasets, build reports from scratch, and recommend dataset applications for existing or new use cases. - Collaborate with data ingestion teams to ensure integration of commercial datasets follows best practices and includes quality checks. - Apply AWS services to support the development and maintenance of scalable data solutions. - Translate business requirements into technical specifications, applying best practices and an enterprise mindset. - Support automation and innovation efforts by leveraging GenAI tools and scalable frameworks. - Contribute to data quality efforts by applying and enhancing existing QC frameworks. - Partner with cross-functional teams to align on business rules and metric definitions. - Assist in data strategy activities such as brand planning, data budget forecasting, and SoW management. - Ensure adherence to data access protocols and compliance standards. **Qualifications & Experience:** - Bachelor's or master's degree in engineering, Statistics, Data Science, or a related field. - Minimum 4-5 years of experience in a Data Analyst role within the biopharma or pharmaceutical industry. - Strong analytical and problem-solving skills. - Effective communication and stakeholder management skills. - Strong proficiency in SQL and Python. - Hands-on experience with BI tools including Power BI and Tableau. - Exposure to platforms such as Domino and Databricks is a plus. - Familiarity with AWS services and cloud-based data engineering practices is a plus. - Experience with GitHub, JIRA, and Confluence is a plus. - Understanding of Data Architecture, ETL processes, and data modeling is a plus. At Bristol Myers Squibb, balance and flexibility in the work environment are recognized, with a wide variety of competitive benefits and programs available to support employees in pursuing their goals. The company values individual talents and unique perspectives, promoting global participation in clinical trials while upholding shared values of passion, innovation, urgency, accountability, inclusion, and integrity. If you find a role that intrigues you, even if it doesn't perfectly align with your resume, Bristol Myers Squibb encourages you to apply. You could be one step away from work that will transform your life and career. As a Commercial Real World Data Analyst at Bristol Myers Squibb, you will have the opportunity to enable data-driven decision-making by translating complex business needs into scalable technical solutions. Your role will involve expertise in commercial pharmaceutical datasets, primarily in Oncology and Haematology, and proficiency in BI tools like Power BI, Tableau, and AWS-based data pipelines. You will be expected to conduct exploratory data analysis with minimal guidance and contribute to broader data strategy efforts, including brand planning, budget forecasting, and Statement of Work (SoW) management. Familiarity with GenAI tools to drive innovation is considered a plus. **Key Responsibilities:** - Develop and maintain dashboards and reports using tools such as Power BI and Tableau to support brand performance tracking, patient journey insights, and forecasting inputs. - Utilize SQL and Python skills, along with therapeutic area knowledge, to conduct exploratory analysis on pharma datasets, build reports from scratch, and recommend dataset applications for existing or new use cases. - Collaborate with data ingestion teams to ensure integration of commercial datasets follows best practices and includes quality checks. - Apply AWS services to support the development and maintenance of scalable data solutions. - Translate business requirements into technical specifications, applying best practices and an enterprise mindset. - Support automation and innovation efforts by leveraging GenAI tools and scalable frameworks. - Contribute to data quality efforts by applying and enhancing existing QC frameworks. - Partner with cross-functional teams to align on business rules and met