mPokket : Senior Data Scientist

Brief Description of position:

About mPokket -

mPokket is a rapidly growing and well-funded fintech startup in the lending domain. We offer micro loans to college students and young professionals via our mobile app. With more than 11 million loans disbursed, we are among the largest and most rapidly growing digital lenders in the country. mPokket has been profitable since 2018 and is adequately funded. In our last Series A round in Feb 2020 we were backed by a US based private equity firm. As we look to scale the business another 10x-20x over the next few years, we are looking for ambitious and talented individuals who want to be part of this amazing journey.

About the role -

As a Senior Data Scientist, you will work as part of our Credit and Analytics Team with key stakeholders to leverage our data to drive operational efficiencies and provide key data-driven insights. You should have a strong problem-solving ability and a knack for statistical analysis. If you’re also able to align our data products with our business goals, we’d 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

  • Ability to deal with ambiguity and competing objectives in a fast paced environment
  • Partner with Product and Operations teams to solve problems and identify trends and opportunities
  • Inform, influence, support, and execute our product decisions and product launches

Work across the following four areas:

Product Operations

  • Designing and evaluating experiments
  • Monitoring key product metrics, understanding root causes of changes in metrics
  • Building key data sets to empower operational and exploratory analysis
  • Evaluating and defining metrics

Exploratory Analysis:

  • Building models of user behaviour for analysis or to power production systems

Product Leadership:

  • Influencing product teams through presentation of data-based recommendations
  • Communicating state of business, experiment results, etc. to product teams
  • Spreading best practices to analytics and product teams

Data Infrastructure:

  • Working with databases such as MySQL, Big Query, Cockroach DB and MongoDB.
  • Automating analyses and authoring pipelines via SQL and Python-based ETL framework

Minimum Qualification

  • Master's degree in Computer Science, Operations Research, Econometrics, Statistics or related technical field
  • 5 to 10 years of experience solving analytical problems using quantitative approaches
  • Experience communicating quantitative analysis results
  • Knowledge with relational databases and SQL
  • Development experience in any scripting language (PHP, Python, Perl, etc.)
  • Knowledge of statistics (e.g., hypothesis testing, regressions)
  • Experience manipulating data sets through statistical software (ex. R, SAS) or other methods

Preferred Qualifications

  • Experience working with distributed computing tools (MapReduce, Hadoop, Hive, etc.)
  • Experience working with large data sets
  • Experience manipulating and analysing high-volume, high-dimensionality data from varying sources
Minimum Work Experience:
5 years
Maximum Work Experience:
10 years
Minimum Qualification:
Maximum CTC (in lakhs per annum):
Mandatory SkillSet:
NOSQL, SQL, Python.


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