AVP - Data Scientist
mPokket is a rapidly growing and well-funded fintech startup in the lending domain. We offer small ticket loans, along with employability solutions, to the low income youth via our mobile app. Started in 2016, mPokket is today among the top 5 fintech lenders in India, having disbursed more than Rs.14,000 crore to 50 lakh borrowers across 19000+ pin codes in India. As we look to scale the business another 10x-20x over the next few years, we are looking for ambitious and talented individuals who will be part of this amazing journey.
We are looking for a AVP to lead a team of data scientist and help us gain useful insight out of raw data.
Responsibilities include managing the data science team, planning projects and building analytics models. You should have a strong problem-solving ability and a knack for statistical analysis. If youre also able to align our data products with our business goals, wed like to meet you. Your ultimate goal will be to help improve our products and business decisions by making the most out of our data.
Key Responsibilities
Responsible for overseeing the data scientists team and data specialists
Teach, lead, and counsel colleagues on new techniques or solutions
Collaborate with data and data engineers to enable deployment of sciences and technologies that will scale across the companys ecosystem
Responsible in developing A-score, B-score, Fraud, collection and marketing models.
Develop the modelling framework, governance and data quality framework along with model risk management.
Maintain the models and periodic validation of the models and solution for optimum performance.
Responsible for the conception, planning, and prioritizing of data projects
Responsible for building analytic systems and predictive models as well as experimenting with new models and techniques
Ensure that data projects align with organizational goals
Minimum Qualification
Master's degree in Computer Science, Operations Research, Econometrics, Statistics or related technical field
10 to 12 years of experience solving analytical problems in lending domain. Experience in developing application scorecard, behaviour scorecard, collection and fraud models.
Experience in developing features from various alternate data sources.
Experience communicating quantitative analysis results and story telling, score analysis and explainability of ML models.
Knowledge with relational databases and SQL
Technical Skills -
Must have
Programming Python
ML model development and validation
ML model deployment and pipeline in AWS
Time series – ARIMA, SARIMA, ARIMAX, Holt-Winters, Multi TS (VAR), UCM
Neural Networks (Deep learning), Naive Bayes
Excel and SQL
Cloud – Understanding of Azure / AWS offerings, Setting up ML pipeline of cloud
Credit risk and Fraud risk management domain knowledge is must
Good to have –
Visualization – Tableau / Power BI / Looker / QlikView
Data management – HDFS, Spark, Advanced Excel
Agile Tools – Azure DevOps, JIRA
Pyspark
Big Data/Hive Database
IDE: Pycharm