Data Exploration
. Understand existing data & reporting by dwelling into multiple
platforms scattered across the organization. You do what it takes to
gather information by connecting with people across business teams and
technology.
Data Analysis & Interpretation
: Conduct in-depth data analysis to identify trends, patterns, and
anomalies in business data. A hands-on approach is essential, demanding
proficiency in a range of tools and technologies to extract, transform,
and analyze data effectively.
Business Knowledge
: Develop business context and knowledge. Proactively seek out best
practices and adopt the same in day-to-day functioning. Navigate team to
use right data, apply right analytical tools and techniques to yield
best in class solution for business
Technical Leadership & Mentorship:
Will provide technical leadership and guidance in the application of
analytical techniques to complex operational problems. Champion the
design, development, and deployment of cutting-edge analytical solutions
that furnish actionable insights to operations teams. Mentor and guide
team members on best practices in data analysis, solutioning.
Stakeholder Management
: Will collaborate closely with operations stakeholders to understand
their specific needs and translate those needs into effective analytical
solutions. Communicate project status, risks, and issues to
stakeholders timely manner. Present findings to stakeholders in a clear
and concise manner.
Project Management
: Drive projects from inception to completion, ensuring adherence to
timelines and budgets, Process documentation, Governance through JIRA
tool.
Speed & Innovate:
Demonstrate hyper speed in performance and Innovation at work to deal
with complex business problem
Governance & Compliance:
Safeguarding the integrity and quality of data underpinning analytical
initiatives, promoting a data-driven culture across the operations
landscape. Establish and maintain appropriate governance processes to
ensure compliance with requirements and internal standards.
Qualifications:
Experience
: At least 8+ years with Master’s as Education background, 10+ years
with Bachelors as Education background experience in the relevant
domain.
Knowledge of database management systems (e.g., DWH, EAP, SQL Server,
Oracle).
Proficiency in data analysis techniques and tools (e.g., SQL, SAS,
Python and Pyspark programming).
Proficient in Formulating Analytical methodology, identifying trends and
patterns with data
Strong analytical, problem-solving skills and ability to drive business
outcomes.
Data Science AI/ML Use case and applications experience
Good understanding of the banking domain, banking products, and
operations in banking.
Excellent communication, interpersonal, and stakeholder management
skills.
Demonstrated ability to drive change and innovation.
Ability to learn quickly and adapt to new tools and technologies.
Proven ability to lead, motivate, and develop high-performing teams.