Retail Specialized Data Scientist

Job Description: You will play a crucial role as a Retail Specialized Data Scientist by utilizing advanced analytics, machine learning, and statistical modeling techniques to enable data-driven decision-making for the retail business. Your responsibilities will involve working closely with various teams to drive business strategies and innovations. The ideal candidate should possess experience in retail analytics and the ability to translate data into actionable insights. Key Responsibilities: - Leverage Retail Knowledge: Utilize your deep understanding of the retail industry to design AI solutions addressing critical business needs. - Gather and clean data from various retail sources like sales transactions, customer interactions, inventory management, website traffic, and marketing campaigns. - Apply machine learning algorithms for classification, clustering, regression, and deep learning to enhance predictive models. - Implement AI-driven techniques for personalization, demand forecasting, and fraud detection. - Utilize advanced statistical methods to optimize existing use cases and develop new products for emerging challenges. - Stay abreast of the latest trends in data science and retail technology. - Collaborate with executives, product managers, and marketing teams to translate insights into actionable business strategies. Qualification Required: - Strong analytical and statistical skills. - Expertise in machine learning and AI. - Experience with retail-specific datasets and KPIs. - Proficiency in data visualization and reporting tools. - Ability to work with large datasets and complex data structures. - Strong communication skills to engage with both technical and non-technical stakeholders. - Solid understanding of the retail business and consumer behavior. - Programming Languages: Python, R, SQL, Scala. - Data Analysis Tools: Pandas, NumPy, Scikit-learn, TensorFlow, Keras. - Visualization Tools: Tableau, Power BI, Matplotlib, Seaborn. - Big Data Technologies: Hadoop, Spark, AWS, Google Cloud. - Databases: SQL, NoSQL (MongoDB, Cassandra). Additional Information: (Omit this section as it does not contain any relevant details about the company) Please note: - Experience: Minimum 3 years of experience required. - Educational Qualification: Bachelors or Master's degree in Data Science, Statistics, Computer Science, Mathematics, or a related field. Job Description: You will play a crucial role as a Retail Specialized Data Scientist by utilizing advanced analytics, machine learning, and statistical modeling techniques to enable data-driven decision-making for the retail business. Your responsibilities will involve working closely with various teams to drive business strategies and innovations. The ideal candidate should possess experience in retail analytics and the ability to translate data into actionable insights. Key Responsibilities: - Leverage Retail Knowledge: Utilize your deep understanding of the retail industry to design AI solutions addressing critical business needs. - Gather and clean data from various retail sources like sales transactions, customer interactions, inventory management, website traffic, and marketing campaigns. - Apply machine learning algorithms for classification, clustering, regression, and deep learning to enhance predictive models. - Implement AI-driven techniques for personalization, demand forecasting, and fraud detection. - Utilize advanced statistical methods to optimize existing use cases and develop new products for emerging challenges. - Stay abreast of the latest trends in data science and retail technology. - Collaborate with executives, product managers, and marketing teams to translate insights into actionable business strategies. Qualification Required: - Strong analytical and statistical skills. - Expertise in machine learning and AI. - Experience with retail-specific datasets and KPIs. - Proficiency in data visualization and reporting tools. - Ability to work with large datasets and complex data structures. - Strong communication skills to engage with both technical and non-technical stakeholders. - Solid understanding of the retail business and consumer behavior. - Programming Languages: Python, R, SQL, Scala. - Data Analysis Tools: Pandas, NumPy, Scikit-learn, TensorFlow, Keras. - Visualization Tools: Tableau, Power BI, Matplotlib, Seaborn. - Big Data Technologies: Hadoop, Spark, AWS, Google Cloud. - Databases: SQL, NoSQL (MongoDB, Cassandra). Additional Information: (Omit this section as it does not contain any relevant details about the company) Please note: - Experience: Minimum 3 years of experience required. - Educational Qualification: Bachelors or Master's degree in Data Science, Statistics, Computer Science, Mathematics, or a related field.