MoneyOnClick - Data Analyst/Senior Data Analyst

At WeRize we are building India's largest financial services brand for the 500 Mn lower middle-income customers in 4000+ small cities (which we call "India 4"). This customer segment has very little penetration of formal loans, insurance or saving products as existing financial service players see this segment as risky and non-profitable. We have created custom lending, insurance and saving products that are tailor-made to serve the needs of India-4 customers.

- To reach these customers at low CAC, we have built a proprietary tech enabled offline- to-online social distribution channel where we have onboarded thousands of financially literate free-lancers such as LIC agents and junior financial sector employees in 1000+ cities. Our fully automated social partner app is available in 6 Indian languages and helps us manage these partners remotely without any physical presence.

- The general perception is that this customer segment is highly risky and non-lendable. We are happy to share that we have been able to maintain near 0% default rates despite Covid19 . Our proprietary ML based family underwriting where we evaluate the P&L of the family and give a joint liability family loan has helped us maintain these low default rates.

- We have achieved Operational profitability and are on-track to reach EBITDA+ by end of 2022 Fund Raise

Funds Raised: $10.25 million

Stage: Series A

Our investors valued the founding team's vision, experience, and depth of understanding of this segment resulting in this fund raise

Investors:

- Kalaari Capital (Indian VC with $850MN AUM and investments such as Myntra, CureFit, Dream11, ElasticRun)

- Picus Capital (Fund run by Alexander Samwer- Co-Founder of Rocket Internet that had multiple billion Dollar + exits/IPOs - Lazada, Jumia, DeliveryHero)

- 3one4 Capital (Early-Stage Fund with $250Mn AUM and companies such as Bank.Open , Licious , Jupiter Neobank in its portfolio)

- Orios Ventures (Early-stage fund with companies like Ola, Pharmeasy and Go Mechanic in its portfolio)

Leadership Team:

Vishal Chopra, Co-Founder & CEO:

- Ex-CBO Lendingkart - India's largest Fintech Lender ($150Mn+ fund raise)

- Fist hire of Amazon India - part of the leadership team that launched Amazon.in

- Regional Director, Souq.com - largest e-commerce player in the Middle East. Raised $425Mn, acquired by Amazon

- MBA, ISB Hyderabad

Himanshu Gupta, Co-Founder & COO:

- Ex-VP and Head of Data Science, Lendingkart - created AI/ML models and maintained NPAs < 2% vs 8% industry avg

- Data Scientist, IHS Markit

- BTech, IIT Delhi

- 14+ years' experience in AI/ML

Founding Team:

Head of Collections:

- South India Head-Collections, Bajaj Finance; managed 800-member team

Head of Product:

- BTech, IIT Kanpur; Product Leader at Lendingkart and Flipkart

Head of Technology:

- Btech CS, IIT Kanpur; Tech Leader at Paytm and Medlife

Head of Business:

- Operations Leader, Lendingkart

Head of Finance: Finance Controller, Navi

Head of Credit Ops: Regional Head, HDB

About the team:

The Data Science team at WeRize plays a critical role in all the decisions both small and big. As a Data Analyst you will be charged with solving various problems in the company using data. Your job doesn't end at finding insights and giving recommendations, you are also responsible for getting your recommendations implemented and ensuring actual business impact.

Some examples of the problem statements that might come to the team:

- How to increase the usage of product X by Y%?

- How to decrease the credit loss in segment X?

- How to increase revenue in segment Y?

About the role:

- As a Data Analyst you will help shape WeRize credit, business and collections strategies by using data driven insights. As a key member of the team, you work closely with leadership, credit, and business teams to craft and execute analytics-driven strategies for business growth.

What are we looking for?

- Excellent coding skills: Python coding (a must skill) and developing SQL queries. (Modelling techniques such as predictive and segmentation model understanding is a plus but not mandatory).

- Prior experience in a fintech in the portfolio, risk or collections team is strong plus.

- Strategic & Analytical Orientation: Exceptional Logical | Analytical | Reasoning skills complemented by rigor and strong quantitative orientation -

- Do you stop at producing the results or do you dive deeper on the why's, how's and ponder on ifs?

- Strong communication skills: Impeccable written and oral communications, coupled with strategic influencing skills and the ability to drive agreement through intellect, interpersonal and negotiation skills

- Can you communicate (present) your results with confidence?

- Strong business judgment, leadership and integrity: She/he should be a tenacious problem solver with good judgment and an open-minded approach. One who pushes the envelope but is rooted in ground reality

- Open to learning new tools & techniques and follow the latest thinking globally in academia and the business world

- Lastly, if you are exceptionally self-driven, motivated and are comfortable with ambiguity.

This is a place for you!

Responsibilities

- Analysis: Identify business challenges and opportunities for improvement and solve for them using business, statistical and data analysis to make strategic recommendations

- Execution: Includes the development of frameworks, hypotheses, tests, analysis and options, scoping operational feasibility, leading implementation efforts and developing a monitoring plan

- Develop data-driven solutions that enhance customer experience, optimize efficiency and mitigate risk.

- Translate data mining results into a clear business-focused deliverable for decision makers

- Knowledge of how to leverage statistical models in algorithms is a plus

- Multivariate analysis: identifying how several parameters can affect retention/behaviour of the customer and identifying actions at different points of the customer lifecycle.

What can you expect?

- Showcasing and honing your skills in a leading fintech with data-driven decision making at its core.

- Work in a challenging environment with one of the best analytical mindset team in the industry.

- Riding the growth bandwagon of a high growth company.

- Flexibility to choose your career path towards Data Science modelling or analytics.

Preferred Qualifications & Experience:

- Level of experience: 1 to 4 years

- BE/MS/PhD/BTech in Computer Science, Engineering, Math, Operations Research, Physics, Statistics or Economics (focus on FinTech is a plus).

- Work experience from similar companies preferred with relevant work experience in Business or Data Analytics.