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Manager,Regional Collections Analytics

Manager,Regional Collections Analytics

ConfidentialBengaluru / Bangalore, India
17 hours ago
Job description

Some Careers Have More Impact Than Others.

If you're looking for a career where you can make a real impression, join HSBC and discover how valued you'll be.

HSBC is one of the largest banking and financial services organisations in the world, with operations in 62 countries and territories. We aim to be where the growth is, enabling businesses to thrive and economies to prosper, and, ultimately, helping people to fulfil their hopes and realise their ambitions.

We are currently seeking an experienced professional to join our team in the role of Manager,Regional Collections Analytics

Principal Responsibilities

  • may include a subset of the listed items, depending on the specific needs of the role
  • Demonstrate excellent analytical ability with conceptual understanding of how Workload Distribution, Productivity, Capacity Planning, SLA work and operation cost in tandem for efficiency. Prepare workforce and capacity summary for management reviews.
  • Act as an SME / consultant on analytical solutioning for the business problem at hand for multiple businesses / regions. Data management and governance using state-of-the-art methods.
  • Create new tools and methodologies and develop recommendations to solve complex analytical problems using various techniques including ML and AI.
  • Develop forecasting models and framework to improve forecast accuracy by incorporating historical trends, new drivers and ongoing enhancement to models
  • Partner with the business effectively to drive data driven decisions and generate value.
  • Communicate proactively to regional and country stakeholders on issues related to variances, workload or capacity and suggest through remediation action.
  • Deliver monthly Governance pack and insights on all KPI and reporting suite.
  • Take direction from line manager in right scoping of projects or adhocs and set right expectation on requirement to avoid conflicts.
  • Can link to the 'bigger picture' and be able to understand the impact of various strategies, policies and events and ability to provide recommendation and guiding team.
  • Build good understanding of business domain, functional goals, and the required technical expertise.
  • Establish quality standards in terms of timeliness of the projects and accuracy of the deliverables.
  • S / he should have analytical independent thought process and can-do attitude towards all the problems needing a solution.
  • Complete other related duties as assigned and support the Company's Diversity programs.
  • Ensure adherence with all the applicable compliance policies (Data security policy, AML, operational risk, Functional manual, Group Compliance Manual, Audit recommendations, Internal Control requirements, regulatory guidelines etc.) and business standards of Organization as applicable. Take timely action on Audit comments and be able to demonstrate compliance with Internal controls.

Leadership & Teamwork

  • Closely interact with the FCS Operations teams from GSC sites and FCS Regions to understand the analytical requirements with minimal handholding and support analytical plan / approach independently to build analytical solutions.
  • Ability to articulate complex analytical findings clearly and concisely to both technical and non-technical audiences, fostering strong relationships with cross-functional teams
  • Proven ability to break down ambiguous business challenges into solvable analytical problems, design effective solutions, and drive them to execution.
  • Demonstrated capability to work effectively in a collaborative environment, contributing to team goals and sharing knowledge.
  • Strong analytical mindset with the ability to critically evaluate information, question assumptions, and continuously seek out new learning opportunities and innovative approaches.
  • Ability to thrive in a dynamic, fast-paced environment, adapt to changing priorities, and maintain effectiveness under pressure.
  • A self-starter with a strong sense of ownership over projects and outcomes, consistently identifying opportunities for improvement and driving initiatives forward.
  • Requirements

    Data Foundation :

  • Strong understanding of data management principles, data governance, and data quality best practices.
  • Proven ability to work with large, complex datasets from various sources.
  • Experience in data extraction, transformation, and loading (ETL) processes.
  • Programming & Big Data Ecosystems

  • Strong programming skills in at least two of the following : SAS, Python, R, SQL, Alteryx, Java - Spring Boot, ReactJS, Tableau, Qlik, Looker, Power BI, or similar platforms (Specific to the role)
  • Hands-on experience with cloud platforms (e.g., Google Cloud Platform (GCP), AWS, Azure) and / or big data ecosystems (e.g., Hadoop).
  • Proficiency with GCP tools like DataProc, BigQuery or similar technologies on other platforms.
  • Experience with distributed computing frameworks such as Spark and Hive SQL (Good to have)
  • Exposure to best coding practices and optimization techniques
  • Operational & Strategic Impact (must-have for mid-level professional)

  • Ability to support and lead governance (strategy and policy) across various analytical initiatives.
  • Experience in spearheading new initiatives in Operations Analytics that drive business value and improve operational efficiency.
  • Applicable to Operations Analytics & Reporting, Model Monitoring and Business Insights (Visualization) roles only

  • Performance Monitoring : Experience in developing and validating analytical models for performance monitoring and risk assessment.
  • Visualization & Dashboards : Prior experience with data visualization and dashboarding tools like Tableau, Qlik, Looker, Power BI, or similar platforms.
  • Problem-Solving : Demonstrated capability to solve unstructured business problems using a data-driven approach and design thinking principles.
  • Proficiency in statistical analysis concepts and their practical application.
  • Applicable to Innovation / Data Science roles only

  • Solid understanding of statistical modelling techniques and their application in an operational context (must have)
  • Experience with Gen AI and machine learning models for classification, regression, and clustering (e.g., Decision Trees, Random Forests, k-NN, Naive Bayes, Gradient Boosting, Artificial Neural Networks).
  • Knowledge of forecasting techniques, market research methodologies, and multivariate analysis tools (e.g., factor analysis, cluster analysis).
  • Should be efficient in prompt engineering techniques like CoT, ToT etc.
  • Understanding and integration of Generative AI concepts, large language models (LLMs), and their potential applications in areas within operational analytics
  • Ability to interpret model results, assess model performance, and explain complex models to non-technical stakeholders
  • Applicable to SmartOps roles only

  • Strong programming skills in Java - Spring Boot, ReactJS or similar platforms
  • Hands-on experience with cloud platforms (e.g., Google Cloud Platform (GCP), AWS, Azure)
  • Fraud & Credit Risk Management : Deep understanding of various fraud schemes, prevention methodologies, and comprehensive knowledge of credit risk assessment across the entire credit lifecycle.
  • Intelligent Automation & Smart Operations : Practical knowledge of Robotic Process Automation (RPA) and broader Smart Operations concepts (integrating AI / ML) for optimizing efficiency, accuracy, and proactive risk management within financial processes.
  • Operational Systems & Data Analytics : Proficiency with core financial operational systems, fraud detection platforms, and leveraging data analytics for monitoring, investigation, and informed decision-making.
  • Preferred Qualifications

    Applies to all roles

  • At least 1-7 years of relevant hands-on experience in Data Analytics / Operation analytics / Work-force management / Capacity Planning / Statistical Modelling & Machine Learning / Visualization & Dashboarding / Java - Web Development / DevOps Tools
  • Familiarity with financial services and banking operations is good to have.
  • Domain Specific Qualifications

  • Operations Analytics and Reporting / Model Monitoring Role – Graduate / Postgraduate degree in quantitative disciplines (e.g., Statistics, Economics, Engineering, Mathematics, Operations Research, Computer Science).
  • Innovation / Data Science Role - Graduate / Postgraduate degree in quantitative disciplines with experience in data science specializing in a relevant field such Machine Learning, Data Mining, Text Mining, Artificial intelligence / Computer Science, NLP and deep learning.
  • SmartOps / Business Insights Role - Graduate / Postgraduate in computer science related field, information systems or other engineering specializations or equivalent.
  • Additional Notes

    This JD is applicable for Analyst as well (overall experience

    You'll achieve more at HSBC

    HSBC is an equal opportunity employer committed to building a culture where all employees are valued, respected and opinions count. We take pride in providing a workplace that fosters continuous professional development, flexible working and, opportunities to grow within an inclusive and diverse environment. We encourage applications from all suitably qualified persons irrespective of, but not limited to, their gender or genetic information, sexual orientation, ethnicity, religion, social status, medical care leave requirements, political affiliation, people with disabilities, color, national origin, veteran status, etc., We consider all applications based on merit and suitability to the role.'

    Personal data held by the Bank relating to employment applications will be used in accordance with our Privacy Statement, which is available on our website.

  • Issued By HSBC Electronic Data Processing (India) Private LTD
  • Skills Required

    Alteryx, Sas, Tableau, Data Governance, Data Management, Python, Aws, BigQuery, Hadoop, Power Bi, Sql, Reactjs, Qlik, Spark, Dataproc, Azure

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