Senior Analyst-Data Science

The Senior Analyst will drive the development and execution of data-driven strategies to improve Sales portfolio performance, working closely with senior leadership across Global Commercial Services (GCS). The position focuses on translating complex data into actionable insights that inform decision-making and support growth. The ideal candidate brings strong analytical curiosity and the ability to distill data into clear, scalable, business-relevant recommendations, combining business acumen with technical expertise. This role partners closely with Sales, Marketing, Finance, Technology, and Capabilities teams to identify opportunities, quantify risks, and prioritize high-impact initiatives. Responsibilities include developing analytical frameworks, advising leadership on performance trends, and enabling effective, data-informed decision-making across the organization.

The Senior Analyst will design, develop, and operationalize ML/AI-powered solutions to enhance client engagement and improve channel efficiency, applying advanced techniques across machine learning, NLP, and generative AI to solve business problems and unlock new growth opportunities. This is a business-facing data science role, with success measured by quantifiable impact. The environment is fast-paced and highly collaborative, requiring strong relationship skills, passion for applied data science, and a singular focus on excellence.

Minimum Qualifications

- 2–3 years of relevant work experience in data science, analytics, or a related quantitative field
- Bachelor’s degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Engineering, Economics, or related discipline)
- Strong analytical and problem-solving skills, with the ability to translate complex, unstructured business problems into quantitative frameworks and models
- Ability to communicate analytical findings and recommendations clearly to technical and non-technical stakeholders
- Experience applying machine learning techniques using standard libraries (e.g., scikit-learn, TensorFlow, PyTorch) to real-world problems; familiarity with NLP tasks such as text classification, summarization, or information extraction
- Strong proficiency in Python and SQL; familiarity with distributed data processing tools (e.g., Spark) is a plus
- Experience working with cloud-based data platforms (e.g., GCP, AWS, or Azure), including data processing and querying tools (e.g., BigQuery)
- Experience with data visualization tools (e.g., matplotlib, seaborn, Tableau) to communicate insights effectively
- Familiarity with data processing workflows (ETL) and version control (e.g., Git)
- Proficiency in Excel and PowerPoint for analysis and presentation of results
- Ability to work independently and collaboratively in a cross-functional environment, with strong attention to detail

Preferred Qualifications

- Master’s degree in a quantitative field (e.g., Data Science, Computer Science, Statistics, Mathematics, Engineering, or related discipline)
- Experience with causal inference or experimentation methods is a plus
- Experience applying machine learning techniques in production environments, including exposure to GenAI approaches (e.g., LLM prompting, retrieval-augmented generation, evaluation methods)