IDFC FIRST Bank is hiring for a fresher entry level Data Analyst role in India

Position:

• Data Analyst

Company:

• IDFC FIRST Bank

Location:

• Mumbai, Maharashtra, India

Job type:

• Full-time

Job mode:

• Onsite

Job requisition id:

• P-178924

Years of experience:

• 0 to 3 years

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Company description:

• IDFC FIRST Bank is one of India’s prominent new-age banks that is focused on customer-centric banking and modern financial solutions.

• The bank is known for its strong values, transparent practices, and digital-first approach, making it a preferred choice among consumers and professionals alike.

• With a mission to create a world-class bank in India, IDFC FIRST Bank offers services across retail, wholesale, and corporate banking.

• Their strategy blends the power of cutting-edge technology with personalized service, enabling sustainable growth and a strong customer base.

• The bank supports a dynamic culture that fosters innovation, encourages learning, and provides career development opportunities across levels.

• With an emphasis on integrity, excellence, and customer focus, IDFC FIRST Bank provides a stable and challenging environment for young professionals starting their careers in analytics, finance, and banking.

• They consistently focus on improving customer experience through data-driven decision-making, and their analytics teams are at the heart of that transformation.

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Profile overview:

• The role is based within the High Performance Enterprise (HPE) vertical under the Data & Analytics function.

• As a Data Analyst in this division, you will work closely with stakeholders to uncover actionable insights that guide strategic decisions.

• You will analyze large sets of structured and unstructured data, extract trends, identify gaps, and present your findings to improve business operations and decision-making.

• This is a role for someone who enjoys problem-solving, has strong analytical thinking, and is capable of translating data into meaningful recommendations.

• You will be expected to scope requirements from multiple teams, understand their business needs, and build solutions using advanced statistical and machine learning methods.

• The bank is seeking someone who has a good balance of technical proficiency and business acumen, along with a curiosity to question the status quo.

• A keen understanding of metrics and success indicators will be crucial, as the role demands measuring the impact of data-driven changes across functions.

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Qualifications:

• A degree in a relevant field such as Computer Science, Mathematics, Statistics, Engineering, or a related quantitative discipline is expected.

• A foundational understanding of data analytics techniques including data cleaning, data wrangling, and data visualization is preferred.

• Familiarity with tools such as Python, R, or SQL for scripting and data analysis tasks is advantageous.

• Exposure to machine learning concepts such as regression, classification, and clustering will strengthen your application.

• Strong Excel and spreadsheet management skills are essential to perform quick analyses and exploratory work.

• Prior internships or academic projects in analytics or data science will be considered valuable.

• Problem-solving ability, critical thinking, and effective communication are must-have soft skills for this role.

• Candidates must show a genuine interest in financial services and eagerness to understand the business implications of data.

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Additional info:

• The job demands regular interaction with business and tech teams, requiring collaboration and proactive communication.

• As a fresher or someone with minimal experience, you will be guided by seniors but are expected to show initiative and curiosity.

• The company expects analysts to question current systems and recommend improvements through data-backed proposals.

• Exposure to end-to-end data analysis from gathering requirements to presenting actionable insights will provide a solid foundation for your analytics career.

• IDFC FIRST Bank offers growth opportunities through internal mobility, learning programs, and mentorship.

• A culture of innovation and performance is deeply rooted in the HPE team’s structure, and new ideas are encouraged and tested regularly.

• This role can be a gateway into more advanced analytics, data engineering, or product analyst positions in the future.

• It’s an ideal opportunity for individuals who are motivated by impact, enjoy working with data, and wish to grow in a high-energy financial environment.

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Key Responsibilities and Duties (Expanded):

Understanding Business Requirements:

• Conduct meetings with business units to understand their current pain points and future goals.

• Clarify ambiguous requirements through discussions and data exploration.

• Break down high-level business challenges into analytical tasks.

• Translate stakeholder expectations into measurable outcomes.

Designing Analytical Solutions:

• Choose appropriate analytical models depending on the problem type and data availability.

• Create data strategies that are both effective and scalable.

• Develop workflows and documentation that outline the analysis framework.

• Prototype models using dummy data before applying them to actual datasets.

Working with Data Structures:

• Understand the data schema and sources feeding into the analytics engine.

• Clean and transform raw data into usable formats using Python, SQL, or Excel.

• Handle missing data, outliers, and anomalies responsibly.

• Ensure the accuracy and integrity of datasets before using them in analysis.

Building Analytical Frameworks:

• Map each business requirement to the right dataset and technique.

• Leverage historical data to predict trends and future behavior.

• Collaborate with data engineers or IT teams for technical support on pipelines.

• Monitor data pipelines for errors or lags that may affect accuracy.

Test and Validate Solutions:

• Develop validation techniques to ensure reliability of outcomes.

• Test the models across time periods, business cycles, or customer segments.

• Iterate quickly when results don’t meet initial expectations.

• Document all tests performed and track changes made.

Apply Machine Learning Techniques:

• Use clustering for customer segmentation.

• Use regression models for revenue predictions or sales forecasts.

• Employ classification models to identify risk or fraud indicators.

• Test different algorithms to determine the most effective solution.

Drive Continuous Improvement:

• Always question if there is a better, faster, or more accurate method.

• Present learnings from past failures as part of improvement culture.

• Be open to feedback and implement learnings in future projects.

• Share knowledge with other analysts to uplift team capability.

Understand Business Impact:

• Present data stories that highlight financial and operational impact.

• Be aware of how every insight could potentially affect customers.

• Make recommendations that align with the overall vision of the bank.

• Track the success of recommendations through key metrics.

Show Initiative and Ownership:

• Be the first to suggest new metrics, dashboards, or reports.

• Take complete ownership of assigned modules or problem statements.

• Participate actively in meetings and cross-functional brainstorms.

• Be dependable and self-managed even as a fresher.

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Key Success Metrics:

• Number of business problems solved through analytics.

• Precision and recall of machine learning models used.

• User satisfaction from internal stakeholders consuming your analysis.

• Ability to reduce turnaround time for repeated analytical requests.

• Clarity and accuracy in presentation of analytical outcomes.

• Consistent tracking of performance across key metrics or KPIs.

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Please click here to apply.