We are seeking an experienced Data Scientist to join a boutique retail team in Cleveland,Ohio. The ideal candidate will bring expertise to drive marketing effectiveness, optimize budget allocation, and enhance overall retail performance. This role involves analyzing customer behavior, evaluating media investments, and developing predictive models to support data-driven decisions across marketing, sales, and operations.
The Data Scientist will play a key role in uncovering insights from complex datasets and collaborating with cross-functional teams to boost customer acquisition, retention, and profitability.
Key Responsibilities:
- Utilize Bayesian Linear Regression techniques to develop advanced predictive models for customer behavior, sales forecasting, and campaign performance.
- Apply media mix modeling to assess the impact of marketing spend across various channels (e.g., TV, digital, social media, print) on sales and customer engagement. Optimize media budget allocation to maximize ROI.
- Analyze customer data to identify key trends in purchasing behavior, preferences, and lifetime value. Create customer segments to inform targeted marketing strategies and personalized experiences.
- Develop attribution models to measure the contribution of different marketing touchpoints (e.g., email, digital ads, in-store promotions) to overall sales and customer engagement.
- Gather and clean data from multiple sources including CRM systems, sales transactions, web analytics, social media, and external market data. Ensure data quality and consistency across platforms.
- Build machine learning models to predict customer churn, optimize pricing strategies, and enhance demand forecasting for retail inventory management.
- Work closely with the marketing, finance, sales, and operations teams to align data-driven strategies with business goals. Communicate insights effectively to both technical and non-technical stakeholders.
- Create dashboards and visualizations using tools such as Power BI, Tableau, or Python to present actionable insights on media effectiveness, customer behavior, and sales trends.
- Design and conduct A/B tests for marketing campaigns, pricing changes, and promotional strategies. Use experimental results to improve decision-making and optimize performance.
- Stay up to date with the latest data science techniques, tools, and retail industry trends. Apply innovative solutions to improve marketing strategies, sales performance, and customer retention.
Qualifications:
- Master’s or Ph.D. in Data Science, Statistics, Applied Mathematics, Computer Science, or a related field.
- 3+ years of experience in a data science role, preferably in retail, marketing, or e-commerce environments.
- Preferred experience with Bayesian Linear Regression and Media Mix Modeling (MMM).
- Proven track record of working with marketing, sales, and customer data.
Technical Skills:
- Proficiency in Python or R for data analysis and modeling.
- Experience with Bayesian modeling frameworks such as PyMC3, Stan, or TensorFlow Probability.
- Expertise in Media Mix Modeling and marketing analytics.
- Solid understanding of SQL for querying large datasets.
- Experience with data visualization tools (e.g., Power BI, Tableau.)
Preferred Qualifications:
- Experience working in retail or e-commerce environments.
- Familiarity with customer relationship management (CRM) systems and web analytics tools
- Experience with time series forecasting and demand planning.
- Knowledge of marketing mix optimization and retail operations management.
