Data Scientist

Role Summary

This role performs deep dive diagnostic, predictive, and prescriptive analytics to support data-driven business decision making and applies advanced data science and big data mining techniques to uncover trends, inform strategic decisions, and drive innovation across various business domains.

Responsibilities

• Develops queries and performs extensive programming to access, transform, and prepare data for statistical modeling.
• Performs deep dive diagnostic, predictive, and prescriptive analytics to support data-driven business decision making.
• Identifies and diagnoses data inconsistencies and errors, documents data assumptions, and forages to fill data gaps.
• Engages with internal stakeholders to understand and probe business processes in order to develop hypotheses. Brings structure to requests and translates requirements into an analytic approach.
• Guides test design, research design, and model validation. Provides statistical consultation services. Serves as the analytics expert on cross functional teams for large strategic initiatives and contributes to the growth of the Vanguard analytic community.
• Prepares and delivers insight presentations and action recommendations. Communicates complex analytical findings and implications to business partners.
• Participates in special projects and performs other duties as assigned.
• Designs and develops data mining protocols and analytical models to identify trends and patterns in large-scale datasets.
• Applies emerging data science methodologies and statistical techniques to provide actionable insights across various business domains.
• Supports innovative research in analytics, contributing to the evolution of data-driven decision-making practices.

• Minimum 5 years of experience in data science, analytics, or statistical modeling roles
• Bachelor's degree (B.E./B.Tech) in relevant fields such as Analytics, Applied Mathematics, Statistics, Computer Science, or a Master's degree/Diploma in a related analytical discipline
• Proficiency in data wrangling and transformation using SQL, Python, or R; strong understanding of statistical modeling and machine learning techniques; experience with tools like Jupyter, SAS, or RStudio
• Hands-on experience in building data mining models, conducting trend analysis, and interpreting complex datasets to support strategic decisions
• Strong communication and visualization skills to translate analytical findings into actionable business insights
• Experience in cloud-based environments (AWS, Azure, or GCP) and using collaboration tools like JIRA, Confluence
• Knowledge of big data platforms and frameworks (Hadoop, Spark) is a plus
• Ability to work cross-functionally and apply analytics to domains such as marketing, operations, or research