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    AVP - Data Science - Bangalore Metropolitan Area, India - mPokket

    mPokket
    mPokket Bangalore Metropolitan Area, India

    Found in: Appcast Linkedin IN C2 - 5 days ago

    Default job background
    Description

    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 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


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