Senior Data Scientist leading data-driven business decision making through advanced analytics. Mentoring junior data scientists while driving innovation across diverse business functions at Vanguard.
Responsibilities
Develops complex queries and performs extensive programming to access, transform, and prepare data for statistical modeling
Leads and executes deep dive diagnostic, predictive, and prescriptive analytics to support data-driven business decision making
Mentors and develops junior data scientists and analysts
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 leaders
Participates in special projects and performs other duties as assigned
Designs scalable data mining models and reporting protocols to identify trends and patterns in massive datasets
Applies modern and emerging data science techniques to solve business problems across functions such as marketing, economics, and operations
Contributes to the advancement of analytics through exploratory research and application of cutting-edge statistical theory
Requirements
Minimum 8 years of experience in data science, predictive analytics, or advanced statistical modeling roles
Bachelor’s degree (B.E./B.Tech) in Analytics, Applied Mathematics, Economics, Statistics, or Computer Science, or a Master’s degree/Diploma in a related quantitative field
Expertise in programming with Python, R, or SQL
Hands-on experience with machine learning libraries (e.g., Scikit-learn, TensorFlow)
Strong understanding of data pipelines, data wrangling, and statistical techniques
Experience in big data environments (Spark/Hadoop)
Familiarity with visualization tools like Tableau or Power BI
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