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Cluster Manager - Payments - Data Science
Bajaj Finserv Health
posted 1mon ago
Job Role Insights
Flexible timing
Key skills for the job
Job Description
Job Purpose
Lead a team responsible for leveraging Business Intelligence Machine Learning to get insights that can be used by Acquiring Businesses to their AOP targets. Duties and Responsibilities
Planning
Engage with the Business Teams to understand their pain points and data needs. Create roadmap of specific tasks initiatives that the team needs to work on. Cascade the tasks and initiatives to the team.
Liaise with various stakeholders including: Acquiring Business Heads.
Business intelligence
Engage with stakeholders to make sure dashboards are utilized correctly
Engage with IT team to ingest new data into EDW
Monitor regularity and accuracy of data flow to the business teams.
Leverage Big Data tools and techniques to build innovative solutions using appropriate modelling techniques
Assist in driving the future development of prediction modelling infrastructure in terms of process, performance and testing
Deliver data insights and BI that are accurate and informative to enable the business to make data-driven content and learner experience decisions
Work with large, complex data sets whilst solving challenging business problems independently and across teams
Define, Build Track Hourly, Daily, Monthly KPIs and work on the plan on how to improve the same.
Initiate Campaigns to drive KPIs to measure the efficiency of the campaigns.
Manage ad-hoc data insights, Trend analysis requests for Sales BIZ teams.
Conduct thorough quality assurance of the data feeds as well as the analytical capabilities
Develop compelling summaries that visualize the data through narrative dashboards to clearly tell a succinct story in easy to understand ways
Demonstrate analytic curiosity and a desire to understand challenges to contribute to matrix team reviews and strategic discussions for insight discovery
Machine Learning
Manage accuracy of Model inventory, ongoing model performance monitoring, model change control, and participate in discussions with Business Heads on model performance
Keep up with the latest developments in CCB/industry in terms of modeling techniques (advanced AI/ML methodologies) products, markets, models, risk management practices and industry standards.
Participate and actively contribute to various process enhancement initiatives for innovations/automation.
Using machine learning tools to select features, create and optimize classifiers
Carrying out preprocessing of structured and unstructured data Key Decisions / Dimensions
Define User Segments and analyze performance of Campaign
Create relevant user segments while analyzing
Data Solutions to Business data problems
Delivery Timeline related.
Adapting Implementing industry best practices
Data Analysis and Value creation
Create insights from predictive statistical modeling, mathematical knowledge, tools, and techniques to solve complex problems and deliver value
Translate business issues into specific requirements to develop analytic solutions, and identify appropriate data to support the solution
Collaborate with Business teams to address business issues and influence change using strategy, industry, and analytical skills Major Challenges
Co-ordination between multiple teams (Business, IT, EDW) and external vendors to enable task delivery
Providing rightful solutions to Business problems with data driven insights
Co-ordination with IT teams for any new development.
Daily sync with EDW team for data quality checks.
Enabling controls on data sanity and build data engineering pipeline.
Collaborate with client stakeholders to understand and frame business requests, determine how best to leverage machine learning and advanced analytic methods (Ensemble models, Decision trees and Neural networks; Operations research; Statistical modeling such as multivariate techniques) to support business objectives
Efficiently construct, develop, and implement the models in a variety of modeling tools, achieving highly accurate models Required Qualifications and Experience
a) Qualifications
Bachelor s Degree in computer science, Math, Physics, Engineering, or related quantitative field or Post-graduate from a reputed institute with a minimum 6 years of experience as a Data Scientist in Fintech/Payment/Relevant Industry.
Work Experience
Minimum of 6 - 8 Years of experience Leading Data Scientists Data Analysis
Experience in implementing machine learning techniques and algorithms, such as, Naive Bayes, SVM, Decision Forests.
Deep learning implementation preferably CNN Open CV
Experience with common data science toolkits, such as Python (Pandas, NumPy, Sci-kit, SciPy etc.)
Great communication skills (ability to convert data language to business language)
Experience with data visualization tools, such as Power BI, PlotLy, Matplotlib etc.
Proficiency in using query languages such as SQL, Spark SQL is mandatory.
Experience with NoSQL databases, such as MongoDB, Cassandra will be a plus
Good, applied statistics skills, such as distributions, statistical testing, regression, etc.
Good scripting and programming skills (Python/R) with OOPs implementation
Lead a team responsible for leveraging Business Intelligence Machine Learning to get insights that can be used by Acquiring Businesses to their AOP targets. Duties and Responsibilities
Planning
Engage with the Business Teams to understand their pain points and data needs. Create roadmap of specific tasks initiatives that the team needs to work on. Cascade the tasks and initiatives to the team.
Liaise with various stakeholders including: Acquiring Business Heads.
Business intelligence
Engage with stakeholders to make sure dashboards are utilized correctly
Engage with IT team to ingest new data into EDW
Monitor regularity and accuracy of data flow to the business teams.
Leverage Big Data tools and techniques to build innovative solutions using appropriate modelling techniques
Assist in driving the future development of prediction modelling infrastructure in terms of process, performance and testing
Deliver data insights and BI that are accurate and informative to enable the business to make data-driven content and learner experience decisions
Work with large, complex data sets whilst solving challenging business problems independently and across teams
Define, Build Track Hourly, Daily, Monthly KPIs and work on the plan on how to improve the same.
Initiate Campaigns to drive KPIs to measure the efficiency of the campaigns.
Manage ad-hoc data insights, Trend analysis requests for Sales BIZ teams.
Conduct thorough quality assurance of the data feeds as well as the analytical capabilities
Develop compelling summaries that visualize the data through narrative dashboards to clearly tell a succinct story in easy to understand ways
Demonstrate analytic curiosity and a desire to understand challenges to contribute to matrix team reviews and strategic discussions for insight discovery
Machine Learning
Manage accuracy of Model inventory, ongoing model performance monitoring, model change control, and participate in discussions with Business Heads on model performance
Keep up with the latest developments in CCB/industry in terms of modeling techniques (advanced AI/ML methodologies) products, markets, models, risk management practices and industry standards.
Participate and actively contribute to various process enhancement initiatives for innovations/automation.
Using machine learning tools to select features, create and optimize classifiers
Carrying out preprocessing of structured and unstructured data Key Decisions / Dimensions
Define User Segments and analyze performance of Campaign
Create relevant user segments while analyzing
Data Solutions to Business data problems
Delivery Timeline related.
Adapting Implementing industry best practices
Data Analysis and Value creation
Create insights from predictive statistical modeling, mathematical knowledge, tools, and techniques to solve complex problems and deliver value
Translate business issues into specific requirements to develop analytic solutions, and identify appropriate data to support the solution
Collaborate with Business teams to address business issues and influence change using strategy, industry, and analytical skills Major Challenges
Co-ordination between multiple teams (Business, IT, EDW) and external vendors to enable task delivery
Providing rightful solutions to Business problems with data driven insights
Co-ordination with IT teams for any new development.
Daily sync with EDW team for data quality checks.
Enabling controls on data sanity and build data engineering pipeline.
Collaborate with client stakeholders to understand and frame business requests, determine how best to leverage machine learning and advanced analytic methods (Ensemble models, Decision trees and Neural networks; Operations research; Statistical modeling such as multivariate techniques) to support business objectives
Efficiently construct, develop, and implement the models in a variety of modeling tools, achieving highly accurate models Required Qualifications and Experience
a) Qualifications
Bachelor s Degree in computer science, Math, Physics, Engineering, or related quantitative field or Post-graduate from a reputed institute with a minimum 6 years of experience as a Data Scientist in Fintech/Payment/Relevant Industry.
Work Experience
Minimum of 6 - 8 Years of experience Leading Data Scientists Data Analysis
Experience in implementing machine learning techniques and algorithms, such as, Naive Bayes, SVM, Decision Forests.
Deep learning implementation preferably CNN Open CV
Experience with common data science toolkits, such as Python (Pandas, NumPy, Sci-kit, SciPy etc.)
Great communication skills (ability to convert data language to business language)
Experience with data visualization tools, such as Power BI, PlotLy, Matplotlib etc.
Proficiency in using query languages such as SQL, Spark SQL is mandatory.
Experience with NoSQL databases, such as MongoDB, Cassandra will be a plus
Good, applied statistics skills, such as distributions, statistical testing, regression, etc.
Good scripting and programming skills (Python/R) with OOPs implementation
Employment Type: Full Time, Permanent
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Cluster Manager salary at Bajaj Finserv Health
reported by
5
employees
with 6-9
years exp.
₹11
L/yr - ₹17.5
L/yr
56%
more
than the average Cluster Manager Salary in India
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What Bajaj Finserv Health employees are saying about work life
based on 180 employees
Flexible timing
Monday to Friday
No travel
Day Shift
Bajaj Finserv Health Benefits
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