Data Analyst

About Credit Saison India

Established in 2019, CS India is one of the country's fastest growing Non-Bank Financial Company (NBFC) lenders, with verticals in wholesale, direct lending and tech-enabled partnerships with Non-Bank Financial Companies (NBFCs) and fintechs. Its tech-enabled model coupled with underwriting capability facilitates lending at scale, meeting India's huge gap for credit, especially with underserved and under penetrated segments of the population.

Credit Saison India is committed to growing as a lender and evolving its offerings in India for the long-term for MSMEs, households, individuals and more. CS India is registered with the Reserve Bank of India (RBI) and has an AAA rating from CRISIL (a subsidiary of S&P Global) and CARE Ratings.

Currently, CS India has a branch network of 45 physical offices, 1.2 million active loans, an AUM of over US$1.5B and an employee base of about 1,000 people.

Credit Saison India (CS India) is part of Saison International, a global financial company with a mission to bring people, partners and technology together, creating resilient and innovative financial solutions for positive impact.

Across its business arms of lending and corporate venture capital, Saison International is committed to being a transformative partner in creating opportunities and enabling the dreams of people.

Based in Singapore, over 1,000 employees work across Saison's global operations spanning Singapore, India, Indonesia, Thailand, Vietnam, Mexico, Brazil.

Saison International is the international headquarters (IHQ) of Credit Saison Company Limited, founded in 1951 and one of Japan's largest lending conglomerates with over 70 years of history and listed on the Tokyo Stock Exchange. The Company has evolved from a credit-card issuer to a diversified financial services provider across payments, leasing, finance, real estate and entertainment.

Roles & Responsibilities:

Develop insights to identify opportunities and drive product strategies. Gain insight into

customer use of current products, untapped opportunities and buyer personas.

Partner with product/business teams to define goals and identify key metrics for existing

features and new releases

Build automated dashboards and reports, craft analyses and tell stories with data to help

our teams make better decisions

Drive awareness and understanding of key metrics and experiment results

Monitor the performance of new features and recommend iterations based on your

findings

Deep dive into assessment of key drivers for KPIs by drawing relevant business

hypothesis and quantify the impact of these drivers on the relevant KPI

Execute deep & complex quantitative analyses that translates data into actionable

insights

Drive data driven decision making through the stakeholders.

Work with complex, non-routine analytical problems, applying advanced methods when

needed.

Influence data-driven decisions across the business spectrum - product/data science

/engineering/finance / partnerships - through end-to-end ownership of projects

Collaborate and coordinate across functions to dissect business, product, growth,

acquisition, retention, and operational metrics.

Required skills & Qualifications:

Bachelor's degree in Computer Science, Engineering or related field from top tier

(IIT/IIIT/NIT/BITS) and work experience with 1-4 years experience in a data analysis

related profile for an internet company

The ability to clearly and effectively communicate the results of complex analyses Is detail oriented, with a strong passion for analytics and problem solving

Is excited to work in a fast paced environment, is comfortable with making decisions

in ambiguity, and has a strong bias for action.

Working knowledge of data mining principles: predictive analytics, mapping,

collecting data from multiple data systems, api frameworks, storage systems on

premises and cloud-based data sources along with strong SQL skills.

Understanding of and experience using analytical concepts and statistical

techniques: hypothesis development, designing tests/experiments, analyzing data,

drawing conclusions, and developing actionable recommendations for business units.

Experience and knowledge of statistical modeling techniques: GLM multiple

regression, logistic regression, log-linear regression, variable selection, etc.

Experience with Excel, Word, and PowerPoint.

Strong background in statistical modeling and experience with statistical tools such

R, Python, Spark, SAS or SPSS.

Able to self-manage your priorities and deliverables while working in a fast-paced,

startup environment

Have hands-on experience with visualization tools (Tableau, PowerBI, Qlikview, D3.Js

)

Any exposure to the Fintech industry, preferably digital lending background, is a

plus.