Chief Data Scientist

**Job Description for Chief Data Scientist (relevant experience: 7-10 years)**
- The finance industry has ignored billions of deserving individuals. We are a mission driven team of finance, analytics and technology professionals, focused on driving financial inclusion to serve the underserved across their credit, savings and financial needs.
- This role will lead a team of data scientists (7/8 members) which is responsible for development, monitoring and driving continuous enhancements to create best in Class models/algorithms to assess risk, churn and uptake across the customer life cycle

**What we look for:
- Expertise in Big Data/ML: Should be able to build cutting edge credit/churn/usage models using advanced algorithms in a Big data/Machine Learning environment. **Should have hands on experience and track record of delivering projects in individual capacity.
- Team Leadership**:Must be able to functionally drive projects with the ability to debug and troubleshoot code modules, specifically fixing logical errors and optimizing code structure of the junior team members. **Should have a track record of leading people effectively by nurturing, motivating and developing the team to drive employee engagement.
- Process oriented: Should help in building a process that maximizes operating efficiency while maintaining risk across multiple lending cycles. There needs to be an obsession with collecting and analyzing data to drive business iterations and improvements.
- Willingness to go above and beyond: For start-ups the responsibilities and needs of the business change quickly. We're looking for someone who is not afraid to take on calculated risks and can deal with ambiguity.

**Responsibilities**:

- Own the end-to-end delivery of models/algorithms across customer life cycle; Develop innovative credit / churn / usage models using mobile wallet transaction data, GSM/CDR and customer bureau data etc
- Define a roadmap for data collection across telcos, credit bureaus, merchant partners & other 3 rd party data sources; deliver on prioritized initiatives to continuously refine models
- Partner with the Data Engineering team to define the required data pipelines to build and enhance the feature bank (foundational capability) to build/deploy the various ML algorithms both for batch and real time use cases
- Collaborate with credit policy/portfolio mgmt. team to drive P&L outcomes. Present data science capabilities with external clients & stakeholders.

**Required Qualifications & Skills:
- Solid expertise in end-to-end risk model lifecycle management (develop, deploy, monitor)
- Previous hands on in (credit or fraud or churn) model development and deployment
- Previous experience in PD model development/validation
- Experience in CSI/PSI model monitoring process
- Hands on experience in data extraction using SQL/Pyspark SQL; data cleaning, feature creation and building models using Py Spark/Python on Spark; Neural network/graph database experience will be a plus
- Experience leading a data science team with functional ownership/responsibilities
- Previous exposure to below algorithms (preferably multiple): Logistic Regression/ Random forest/ XGBOOST
- Strategy performance tracking and swap in / swap out analysis
- **Good to have**:

- Good business understanding of the fintech/consumer finance space
- Experience in working with credit card / personal lending space, esp fintech or Telecom industry