Senior Data Analyst

Job description:

Role Purpose & Objective:

The Data Analyst is responsible for advising the business on the potential of data to provide new insights into the business's mission.

• Take initiatives and ideate analytics projects which have scope for incremental revenue, reducing cost, and increased operational efficiency.
• Support in creating custom reports and presentations accompanied by strong data visualization and storytelling to drive necessary data-driven actions.
• The candidate will need to be able to effectively communicate the intended processes and provide a clear understanding of what data is required and available.
• Transform and reformat data into a usable structure for analysis.
• Prepare comprehensive reports that effectively communicate findings, insights, and recommendations to both technical and non-technical stakeholders.
• Collaborate with cross-functional teams (e.g., Sales, Finance, Risk, and Credit) to understand business requirements and validate data.

Size of the Role:

• 10 - 50 BAU monthly reports.
• 30 - 100 monthly SRs handling.
• Coordinate with stakeholders.
• Exception reports and report automation.
• Maintain agreed TAT for SRs and BAUs.
• Handle 1 - 3 projects like SLBC, EDR, PSLC, Bureau reporting, etc.

Key Duties & Responsibilities of the Role:

• Identify and gather data from various sources (databases, spreadsheets, APIs, web scraping, etc.).
• Clean data and handle missing, duplicate, or inconsistent values.
• Transform and reformat data into a usable structure for analysis.
• Prepare comprehensive reports that effectively communicate findings, insights, and recommendations to both technical and non-technical stakeholders.
• Ensure data quality and integrity.
• Identify areas to increase efficiency and optimize data collection and analysis processes.
• Establish and monitor Key Performance Indicators (KPIs) and other metrics to measure business performance.
• Present findings in an understandable and actionable manner.
• Engage with business stakeholders to understand their business process and translate business problems into analytical structures using visualization tools.
• Maintain a high level of engagement with business. Periodically prepare and communicate learning from business trends to ensure enhancements in business growth projections and track them against actual business.
• Collaborate with Senior Data Scientist/Senior Data Analysts to communicate obstacles and findings to relevant stakeholders in an effort to improve decision making and drive business performance.
• Develop and provide a set of regular MIS, KPIs, key drivers, and portfolio data across all product and segment areas.
• Set up the analytical capability in providing value-added analysis and MIS review for the product and distribution groups.
• Monitor product performance and competitive environment; highlight important trends, gaps, and opportunities for the business; cost-effective marketing, repricing, or fee opportunities.
• Design, develop, and distribute operational and qualitative reporting to provide stakeholders with consistent insights into regulatory matters and operational progress.
• Produce periodic and ad-hoc senior management and stakeholder reports with appropriate controls over manual, semi-automated, and automated reporting functions.

Customer (Both Internal & External):

• Support infrastructure setup for analytics-driven initiatives of the bank.
• Ensure timely delivery of required reports to the business team.
• Ensure data accuracy while submitting data to external stakeholders like RBI and Credit Bureau.
• Liaise with IT/DW/Operations departments to ensure accuracy of the data and data governance management through customized MIS and quality management for reliable outcomes for consumption.
• Ensure all deliverables are followed through maker and checker process.

Internal Process:

• Liaise with IT/DW/Operations departments to ensure accuracy of the data and data governance management through customized MIS and quality management for reliable outcomes for consumption.
• Constantly look for increasing the efficiency of the team and department resulting in reducing TAT of analytics projects, e.g. process enhancement, automation, etc.

Innovation & Learning:

• Upskill to new-age technologies with respect to data analytics. Enhance on-the-job self-learning related to analytics techniques/tools.
• Ensure timely completion of training/learning programs assigned from time to time.
• Upskill to new-age technologies with respect to customer segmentation and business tracking. Enhance on-the-job self-learning related to analytics techniques/tools.

Minimum Requirements of Knowledge & Skills:

Educational Qualifications:

• BE/B.Tech or MCA or equivalent degree.

Experience (Years and Core Experience Type):

• Overall experience of 3 - 5 years, preferably in the BFSI domain, with specific experience in data analytics and data handling skills.
• Experience in using tools such as SQL, Python, Tableau, Excel, etc.
• Experience with cleaning, transforming, and visualizing large data sets in various data formats (e.g. unstructured logs, XML, JSON, flat files, Avro, Parquet).
• Knowledge of Big Data ecosystem tools (e.g. Hadoop, Hive, Spark, Kafka).
• Solid SQL skills for querying relational databases (e.g. SQL Server, DB2, MySQL, Oracle).

Certifications:

• Certifications in SQL, Python, and Tableau.
• Certifications in AI/ML.
• Certifications in data management and data handling.

Functional Skills:

• Good in MS Office and data analysis/building reports.
• Knowledge of CRM application, Finacle, and other banking applications.
• Eye for detail and reading numbers.
• High business acumen with good understanding of banking operations across all channels.
• Solid interpersonal and communication skills with ability to build strategic relationships, influence stakeholders, and deliver presentations to executive audience.

Behavioral Skills:

• Teamwork.
• Decision making.
• Assertiveness.
• Structured thinker, effective communicator with excellent written communication skills.
• Ability to understand organizational dynamics.
• Ability to work with a cross-functional team.
• Excellent people management and stakeholder management skills.
• Good analytical and presentation skills.
• Proficiency in English written and verbal communication skills.

Competencies:

• Cross-functional engagement.
• Vendor management.
• Problem solving.
• Understanding of the financial sector to recognize and drive forward opportunities where data science can transform the bank.
• Skilled at influencing and communicating to various stakeholders up to executive level.

Key Interactions:

• All Functional Heads (Business & Support Functions) and their teams.
• Data Science & Decision Management team members.
• Data Warehouse team.
• Third-party service providers.
• Credit Bureaus.

Skills

Python, SQL, Tableau