Product Analytics - Deputy Manager - Recharges & Utilities

Role Overview: You will be joining Paytm as a Data Science Consultant, responsible for showcasing the value of analytics in making informed business decisions. Your primary focus will be on developing and deploying Data/Statistical models to provide data-driven insights to business stakeholders. Your expertise in Data Science & Machine Learning will be instrumental in decoding user behavior. Key Responsibilities: - Find innovative ways to acquire users both within and outside the Paytm ecosystem. - Analyze the behavior of loyal users on the app based on variables such as transaction type, payment mode, balance checking frequency, and demographic information. - Develop statistical models to identify users with traits similar to loyal users from Paytm's active user base. - Segment users based on the percentage of their characteristics matching with loyal users. - Act as a brand ambassador for Paytm by embodying the values of 'Stay Hungry, Stay Humble, Stay Relevant.' Qualifications Required: - 1-4 years of experience in Data Science projects. - Proficiency in statistical modeling of large datasets. - Expertise in Python, R language, and deep knowledge of ML packages. - Proficient in fetching data from SQL. - Knowledge of AWS would be advantageous. - Strong structural and analytical thinking. - Ability to structure and execute data science projects end to end. - Experience with data science toolkits such as Python, NumPy, Pandas, etc. - Experience in automating analysis and authoring pipelines using SQL, NoSQL, and Python-based ETL frameworks. Company Details (if available): Paytm offers a collaborative output-driven environment that fosters cohesiveness across businesses through technology. You have the opportunity to increase cross-sell opportunities and enhance the average revenue per user. You will receive 360 feedback from peer teams on your support towards their goals. At Paytm, respect is earned and not demanded from your peers and manager. Note: Compensation details have not been provided in the job description. Role Overview: You will be joining Paytm as a Data Science Consultant, responsible for showcasing the value of analytics in making informed business decisions. Your primary focus will be on developing and deploying Data/Statistical models to provide data-driven insights to business stakeholders. Your expertise in Data Science & Machine Learning will be instrumental in decoding user behavior. Key Responsibilities: - Find innovative ways to acquire users both within and outside the Paytm ecosystem. - Analyze the behavior of loyal users on the app based on variables such as transaction type, payment mode, balance checking frequency, and demographic information. - Develop statistical models to identify users with traits similar to loyal users from Paytm's active user base. - Segment users based on the percentage of their characteristics matching with loyal users. - Act as a brand ambassador for Paytm by embodying the values of 'Stay Hungry, Stay Humble, Stay Relevant.' Qualifications Required: - 1-4 years of experience in Data Science projects. - Proficiency in statistical modeling of large datasets. - Expertise in Python, R language, and deep knowledge of ML packages. - Proficient in fetching data from SQL. - Knowledge of AWS would be advantageous. - Strong structural and analytical thinking. - Ability to structure and execute data science projects end to end. - Experience with data science toolkits such as Python, NumPy, Pandas, etc. - Experience in automating analysis and authoring pipelines using SQL, NoSQL, and Python-based ETL frameworks. Company Details (if available): Paytm offers a collaborative output-driven environment that fosters cohesiveness across businesses through technology. You have the opportunity to increase cross-sell opportunities and enhance the average revenue per user. You will receive 360 feedback from peer teams on your support towards their goals. At Paytm, respect is earned and not demanded from your peers and manager. Note: Compensation details have not been provided in the job description.