Live opening · Posted 1 day ago

Cluster Manager - Risk/Senior Cluster Manager - Risk

Bajaj Finserv · Pune Division, Maharashtra, India (On-site)
Linkedin No
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At a glance

The key details from the original listing.

Posted 1 day ago
CompanyBajaj Finserv
LocationPune Division, Maharashtra, India (On-site)
Work modeNo
SourceLinkedin
Listed1 day ago

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About the role

Description supplied by the original job listing.

Location Name: Pune Corporate Office - Fountainhead
Job Purpose
“This position is open with Bajaj Finance ltd.”
Manage and enrich Franchise customer data of 45 Cr to enable creation and generation of Pre-Approved offers, improve Approval rates by enriching data through verified sources and enable instant disbursals by continuously improving fill rates of verified information to help scale volumes in 3in1 App.
Responsible for identifying data requirements and evaluating quality of data sourced through external vendors.
This capability will help build scale on 3in1 App of the Company and targets to improve Market share of the Company by 10% from current levels at the same portfolio risk levels
Duties And Responsibilities
PRINCIPAL ACCOUNTABILITIES
(Accountabilities associated with the job)
Data Quality, Data Standardization & New Data Enrichment Management
o Data Standardization & Data Quality
o Ensure all Existing & Prospect records are maintained in a single repository
o All other data points related to these records and any data enrichment to be maintained in a single repository
o Define SOP & rules for duplicate identification and resolution
o Define validation rules for data fields to ensure that junk data does not enter the repository
o Prepare BRD and User Story for development of Internal Data Storage design that enables to maintain every data point received with tagging of Source, time, Verified / Non-Verified data and Confidence level of the same.
o Define field quality validations and create data quality index
o Define logic for flagging of Confidence levels for the data fields to enable end users of the data to use the data as per their confidence flagging
o Governance of New Data element or New Data Source
o Work with IT BIU team in creation of Real Time Data Quality dashboards
o Responsible for ensuring error rates in Data Quality are maintained within threshold levels
o Work with IT BIU team in creation of Data Confidence & Fill Rate dashboards
o Define SOP and scope of activities for Data Quality management through Manual intervention to be executed through outsourced Credit Ops shop in Bareily
o Control checks on data quality management done through Bareily shop
o Define validation rules and confidence levels for any variable brought into the single repository
o Responsible to ensure that the data tables have no data quality issues
o Data Enrichment
o Engage with Partnership team in validating the information is meeting the quality standards that have been defined
o Will qualify whether data points from a Particular Partner or Source can be used for Enrichment
o Will also identify and maintain list of sources, websites which are to be used for Data Enrichment
Stakeholder Management
Setup and convene Change Control Board meeting with all stake holders across all businesses and functions
Engaging with Data Partnership team for Data quality and Data Offer team for usage of data for offer generation
Engaging with EDW team for creating and managing tables
Team development
Identify the right talent at positions within the function
Establish individual performance expectations and regularly review individual performance of the team
Identify development needs of teams and provide appropriate opportunities (trainings for professional development etc.) to ensure teams are motivated and equipped to drive business
Ucational Qualifications
Required Qualifications and Experience
Qualifications
Post-graduation/ MBA/ Educational background in mathematical, statistical and data science orientations
Work Experience
Minimum 7+ years of experience in EDW management
Experience with large data handling and quantitative analysis
Exposure to data analytics tools (Eg. SAS, SQL and Decision Tree) automated BI reports
Strong Problem-solving ability and analytical skills

Work arrangement
No

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