Data Analytics – Creditas (Gurgaon)

Data Analyst / Senior Data Analyst

Company: Creditas Solutions
Location: Gurugram, Haryana
Experience: 2–6 Years
Mandatory Skills: SQL and Python
Immediate Joiners Preferred

About Creditas

Creditas Solutions is a leading fintech company headquartered in Gurgaon, partnering with top banks across India. The organization is focused on building scalable, tech-driven solutions that enhance customer experience and drive business outcomes in the financial ecosystem.

Role Overview

We are looking for a skilled and analytical Data Analyst / Senior Data Analyst to join our Analytics team at Creditas.

The role involves working with large datasets, developing scalable analytical solutions, building predictive models, and delivering actionable business insights. The candidate will work closely with Product, Business, and Operations teams to enable data-driven decision-making and identify opportunities for business growth.

The ideal candidate must have strong hands-on expertise in SQL and Python, along with excellent analytical and problem-solving skills.

Key Responsibilities

Analyze large and complex datasets to identify trends, patterns, business opportunities, and actionable insights.
Develop, optimize, and maintain complex SQL queries for data extraction, transformation, and analysis.
Use Python for data manipulation, analysis, automation, and predictive modelling.
Design, develop, and maintain analytical dashboards, reports, and business performance trackers.
Build and optimize analytical and predictive models to support business decisions and improve outcomes.
Perform deep-dive analysis of customer journeys, product performance, conversion funnels, and business metrics.
Collaborate with Product, Business, and Operations teams to understand requirements and deliver data-driven solutions.
Identify process inefficiencies, business gaps, and growth opportunities through data analysis.
Ensure data accuracy, consistency, and reliability across analytical outputs and reporting.
Present analytical findings and recommendations to stakeholders in a clear and structured manner.

Qualifications & Experience

2–6 years of relevant experience in Data Analytics, Business Analytics, or Data Science, preferably in fintech, banking, or financial services.
Strong proficiency in SQL and Python is mandatory.
Hands-on experience working with large datasets and complex data structures.
Strong experience in Python libraries such as Pandas, NumPy, and Scikit-learn.
Experience in data visualization and reporting tools such as Power BI, Tableau, or similar.
Understanding of statistical analysis, predictive modelling, and machine learning concepts.
Ability to translate business requirements into analytical solutions and actionable insights.
Strong analytical thinking, problem-solving, and attention to detail.
Excellent communication skills and the ability to work with cross-functional stakeholders.
Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Engineering, Data Science, or a related field.

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Role Overview

We are looking for a skilled and analytical Data Analyst / Senior Data Analyst to join our Analytics team at Creditas.

The ideal candidate must have strong hands-on expertise in SQL and Python, along with excellent analytical and problem-solving skills.

Key Responsibilities

Analyze large and complex datasets to identify trends, patterns, business opportunities, and actionable insights.

Develop, optimize, and maintain complex SQL queries for data extraction, transformation, and analysis.

Use Python for data manipulation, analysis, automation, and predictive modelling.

Design, develop, and maintain analytical dashboards, reports, and business performance trackers.

Build and optimize analytical and predictive models to support business decisions and improve outcomes.

Perform deep-dive analysis of customer journeys, product performance, conversion funnels, and business metrics.

Collaborate with Product, Business, and Operations teams to understand requirements and deliver data-driven solutions.

Identify process inefficiencies, business gaps, and growth opportunities through data analysis.

Ensure data accuracy, consistency, and reliability across analytical outputs and reporting.

Present analytical findings and recommendations to stakeholders in a clear and structured manner.

Qualifications & Experience

2–6 years of relevant experience in Data Analytics, Business Analytics, or Data Science, preferably in fintech, banking, or financial services.

Strong proficiency in SQL and Python is mandatory.

Hands-on experience working with large datasets and complex data structures.

Strong experience in Python libraries such as Pandas, NumPy, and Scikit-learn.

Experience in data visualization and reporting tools such as Power BI, Tableau, or similar.

Understanding of statistical analysis, predictive modelling, and machine learning concepts.

Ability to translate business requirements into analytical solutions and actionable insights.

Strong analytical thinking, problem-solving, and attention to detail.

Excellent communication skills and the ability to work with cross-functional stakeholders.

Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Engineering, Data Science, or a related field.