
Data Scientist (Econometrics)-Vice President
- New York City, NY
- Permanent
- Full-time
- Design, develop, and implement advanced econometric models to evaluate the impact of policies, programs, and business interventions
- Create schemas to model relationships and speed analytics
- Collect, clean, and analyze large, often messy, datasets from various sources
- Utilize statistical software and programming languages to conduct rigorous data analysis and ensure data quality and integrity
- Develop and deploy predictive models using a range of machine learning techniques to forecast key economic and business metrics, such as demand, market trends, and customer behavior
- Translate complex quantitative findings into clear, concise, and actionable recommendations for senior leadership and cross-functional teams
- Create compelling data visualizations and presentations to communicate insights effectively
- Collaborate with product managers, engineers, and business leaders to define business problems, formulate hypotheses, and translate analytical findings into strategic decisions and product improvements
- Stay current with the latest advancements in data science, econometrics, and machine learning
- Develop and refine internal tools and frameworks to scale econometric analysis across the organization
- Master's or Ph.D. in Economics, Econometrics, Statistics, Computer Science, or a related quantitative field
- 6 years' experience working in an advanced analytical role with at least 2 years related to economic data
- Proficiency with statistical programming languages, particularly Python (with libraries like Pandas, NumPy, Scikit-learn) and/or R
- Skilled using SQL for data extraction, manipulation, and analysis
- Competent with data visualization tools (e.g., Tableau, Power BI)
- Ability to deploy advanced methods in econometrics and quickly translate and communicate microeconomic and macroeconomic trends in consumer & business data
- Robust knowledge and practical approach to market economics & econometric modeling of economic relationships
- Fundamental understanding & appreciation of consumer financial health frameworks and consumer segmentation methodologies
- Comprehensive knowledge of time-Series (e.g., Seasonal Decomposition, ARIMAX, VAR, ECM) and classification (e.g., Logistic regression)
- Exceptional analytical and problem-solving skills with the ability to break down complex business problems into manageable analytical frameworks
- Excellent written and verbal communication skills to explain technical concepts to diverse audiences
- Familiarity with consumer and small business datasets
- Experience with big data environments such as Hadoop and Spark
- Knowledge of cloud-based platforms (e.g., AWS, GCP)