Job Description

About Us: 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. : We are looking for a Technical Lead level Data Scientist that will help us discover the information hidden in our terabytes of transactional, demographic, and user behavior data. You will help us make smarter decisions to deliver even better products that help our customers. Your primary focus will be in applying data mining techniques, doing statistical analysis, and building high quality machine learning systems integrated into our real time software systems and microservices. Some of the problems we are trying to solve include prediction of discounting and offer levels that balance customer gratification and profitability, and creation of a data platform that can help create meaningful offers in the customer lifecycle. Requirements: Machine learning experience of 6-8 years of implementing and successfully deploying ML solutions at scale for real-world problems. Experience working on regression and classification algos is preferred. Domain experience related to Food e-commerce, Fashion retail or any business use case where problems have been solved at customer level will be prefered Selecting features, building and optimizing ML models using various techniques Data mining at petabyte scale and working with our data engineering team. Extending company\'s data with third party sources of information when needed Enhancing data collection to include information relevant for building analytic systems Processing, cleansing, and verifying the integrity of data used for ML analysis Creating and tuning ML models for various initiatives. Own the application of machine learning algorithms. Design and evaluate novel approaches for handling high-volume real-time data streams in a machine learning environment. Develop a feedback system to improve the selection of features for the algorithms. Understand the theory and application of theory for common classification, clustering, regression and collaborative filtering. Identify valuable data sources and automate collection processes Undertake preprocessing of structured and unstructured data Present information using data visualization techniques Propose solutions and strategies to business challenges Collaborate with engineering and product development teams Curiosity to learn and implement latest developments in the field of data science Skills & Tools: Expertise in Python, specifically, usage of Python libraries and add-ons for data, math, and machine learning. Expertise in working with notebooks like R, Jupyter, etc. Ability to script and write small programs. Data visualization experience with web frontend libraries. Data ETL from SQL and NoSQL sources. Good statistical skills. Bachelors in Engineering or Masters degree with 6 to 8 years of relevant experience. Experience in distributed data processing frameworks like Hadoop, Spark or other similar frameworks is a plus Java, Scala or any other high level languages are a bonus. You understand what it takes to deliver ML predictions in real time online applications. Usage or know-how of FastAPI Working knowledge of AWS or any other cloud platform is a plus.

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