About Paytm:
Paytm is India’s leading digital payments and financial services company, which is focused on driving consumers and merchants to its platform by offering them a variety of payment use cases. Paytm provides consumers with services like utility payments and money transfers, while empowering them to pay via Paytm Payment Instruments (PPI) like Paytm Wallet, Paytm UPI, Paytm Payments Bank Netbanking, Paytm FASTag and Paytm Postpaid – Buy Now, Pay Later. To merchants, Paytm offers acquiring devices like Soundbox, EDC, QR and Payment Gateway where payment aggregation is done through PPI and also other banks’ financial instruments. To further enhance merchants’ business, Paytm offers merchants commerce services through advertising and Paytm Mini app store. Operating on this platform leverage, the company then offers credit services such as merchant loans, personal loans and BNPL, sourced by its financial partners.
Requirements:
Bachelor’s degree in technical/ analytics/ data science/ mathematics/ statistics/ economics/ operations research field or equivalent preferred
Experience of 6 months – 3 years of working in BFSI/ Fintech/ Digital/ Retail analytics and Business Insights/reporting
Expertise in some of the analytics tools/languages such as: SQL/ Python/ PySpark/ Excel/ R/ Hadoop/ Hive etc., or equivalent technologies with a strong desire and ability to learn new technologies and concepts
Understanding and/or experience of technical and analytical approaches, predictive modelling, multivariate testing, and statistical principles
Ability to handle, advocate and represent a variety of complex priorities, weighing the value to Target and the teams you support
Excellent Data Handling Skills including Efficient Raw Data Querying, Data Cleaning, Data-Pre-Processing, Data-Massaging, Data Wrangling and Data Transformation.Good working knowledge of concepts of Variable and Dimensionality reduction, Variable creation/ transformation, Feature Engineering
Expertise in analyzing huge data (structured and unstructured) using statistical and data modeling tools such as SQL, Python, R/ PySpark/ SAS as well as Data Visualization and Presentation via Executive Dashboards with Power BI, Tableau, Qlikview or similar data-visualization software.
Responsibility:
The ideal candidate should be self-directed, passionate about data, ready for an immersive, real-world experience and focused on delivering the right results.
The candidate should be able to apply programming acumen and a breadth of tools, data sources and analytical techniques to answer a wide range of high-impact business questions and present the insights in a concise and effective manner.
Technical aptitude, programming, reporting/data visualization and data science skills are required in this role. The role requires incubating, developing, testing, and iteratively improving data analyses to provide key insights that will shape product actions, improve customer experience, and usage of the product(s).