Data Scientist
Data Scientist
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5years
Not Disclosed
Salary Not Disclosed
1 Vacancy
Job Description
- Conduct product assortment analysis identify trends and patterns in category performance and support new product launches.
- Utilize data and visualization techniques to provide actionable insights for store teams territory and district managers.
- Design and test campaign effectiveness analyze crosssell and upsell opportunities and perform Market Basket Analysis.
- Analyze loyalty and customer data to design direct marketing campaigns and measure their effectiveness.
- Translate complex data insights into understandable and actionable information for nontechnical and business teams.
Requirements
- Proven experience as a Data Scientist or similar role.
- Strong knowledge of data analysis statistics and machine learning.
- Proficiency in data science tools and programming languages such as Python R Azure Databricks SQL etc.
- Familiarity with:
- Supervised and unsupervised learning techniques
- Deep learning and reinforcement learning
- Evaluation metrics feature engineering model selection and validation ensemble methods and explainable AI
- Category/Product AnalyticsStore AnalyticsMarketing and Promotion AnalyticsCustomer Analytics
- Expertise in visualization tools such as Power BI Spot fire or similar.
- Excellent storytelling skills to explain complex data to nontechnical/business teams
- Experience in analytics preferably within Retail CPG or Ecommerce domains.
- Excellent communication and collaboration skills with the ability to work effectively in a team environment.
Benefits
- Competitive salary and performancebased bonuses.
- Comprehensive insurance plans.
- Collaborative and supportive work environment.
- Chance to learn and grow with a talented team.
- A positive and fun work environment.
Proven experience as a Data Scientist or similar role. Strong knowledge of data analysis, statistics, and machine learning. Proficiency in data science tools and programming languages such as Python, R, Azure Data-bricks, SQL, etc. Familiarity with: Supervised and unsupervised learning techniques Deep learning and reinforcement learning Evaluation metrics, feature engineering, model selection and validation, ensemble methods, and explainable AI Category/Product Analytics,Store Analytics,Marketing and Promotion Analytics,Customer Analytics Expertise in visualization tools such as Power BI, Spot fire, or similar. Excellent storytelling skills to explain complex data to non-technical/business teams Experience in analytics, preferably within Retail, CPG, or E-commerce domains. Excellent communication and collaboration skills with the ability to work effectively in a team environment.
Employment Type
Full Time
