Vice President
Published date: 2024/01/10
- Location: New Delhi, Delhi, India
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Vice President
Mashreq Bank
New Delhi, Delhi
Apply
10 hours ago
Full–time
Job Purpose
Data & Analytics team is responsible to integrate new data sources and build data models, data dictionaries and machine learning models for the Wholesale Bank.
The goal is to design and build data products to support squads in Wholesale Bank with business outcomes and development of business insights.
In this Job Family we make a distinction between Data Analysts and Data Scientist.
Both scientists as analysts work with data and are expected to write queries, work with engineering teams to source the right data, perform data munging (getting data into the correct format, convenient for analysis/interpretation) and derive information from data.
The data analyst typically works on simpler structured SQL or similar databases or with other BI tools/packages.
The Data Scientists are expected to build statistical models or be hands-on in machine learning and advanced programming.
Role of Data Scientist is to support our Corporate Banking teams with insights gained from analyzing company data.
The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action.
They must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations.
They must have banking or corporate banking experience.
Key Result Areas
Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques, and business strategies
Use both predictive & AI/ML modeling techniques to increase and optimize customer experiences, revenue generation, ad targeting, and more
Develop custom data models and algorithms
Develop processes and tools to monitor and analyze model performance and data accuracy
Assess the effectiveness and accuracy of new data sources and data-gathering techniques
Develop company A/B testing framework and test model quality
Coordinate with different functional teams to implement models and monitor outcomes.
Operating Environment, Framework and Boundaries, Working Relationships
Develops data products that are fit for purpose by leveraging advanced data and analytical tools and technology in order to help customers to make the best possible financial decision and to make the organization more data driven, taking into account the data privacy legislations and ethical boundaries.
Combines IT and data management expertise.
He / she develops algorithms to apply to external and internal data to predict customer needs and / or developments in markets, industries and the wider financial landscape.
Linking pin and liaison towards the Data Engineers
Problem Solving
Should be comfortable in solving Wholesale Banking domain analytical solution within AI/ML platform
Decision Making Authority & Responsibility
Knowledge, Skills and Experience
Master's or Ph.
D.
in statistics, mathematics, or computer science
Experience using statistical computer languages such as R, Python, SQL, etc.
Experience in statistical and data mining techniques, including generalized linear model/regression, random forest, boosting, trees, text mining, social network analysis
Experience working with and creating data architectures
Knowledge of machine learning techniques such as clustering, decision tree learning, and artificial neural networks
Knowledge of advanced statistical techniques and concepts, including regression, properties of distributions, and statistical tests
6+ years of experience manipulating data sets and building statistical models
Experience using web services:
Azure AI/ML , Redshift, S3, Spark, DigitalOcean, etc.
Experience analyzing data from third-party providers, including Google Analytics, Site Catalyst, Core metrics, AdWords, Crimson Hexagon, Facebook Insights, etc.
Experience with distributed data/computing tools:
Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
Experience visualizing/presenting data for stakeholders using: Periscope, Business Objects, D3, ggplot, etc
Vice President
Mashreq Bank
New Delhi, Delhi
Apply
10 hours ago
Full–time
Job Purpose
Data & Analytics team is responsible to integrate new data sources and build data models, data dictionaries and machine learning models for the Wholesale Bank.
The goal is to design and build data products to support squads in Wholesale Bank with business outcomes and development of business insights.
In this Job Family we make a distinction between Data Analysts and Data Scientist.
Both scientists as analysts work with data and are expected to write queries, work with engineering teams to source the right data, perform data munging (getting data into the correct format, convenient for analysis/interpretation) and derive information from data.
The data analyst typically works on simpler structured SQL or similar databases or with other BI tools/packages.
The Data Scientists are expected to build statistical models or be hands-on in machine learning and advanced programming.
Role of Data Scientist is to support our Corporate Banking teams with insights gained from analyzing company data.
The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action.
They must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations.
They must have banking or corporate banking experience.
Key Result Areas
Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques, and business strategies
Use both predictive & AI/ML modeling techniques to increase and optimize customer experiences, revenue generation, ad targeting, and more
Develop custom data models and algorithms
Develop processes and tools to monitor and analyze model performance and data accuracy
Assess the effectiveness and accuracy of new data sources and data-gathering techniques
Develop company A/B testing framework and test model quality
Coordinate with different functional teams to implement models and monitor outcomes.
Operating Environment, Framework and Boundaries, Working Relationships
Develops data products that are fit for purpose by leveraging advanced data and analytical tools and technology in order to help customers to make the best possible financial decision and to make the organization more data driven, taking into account the data privacy legislations and ethical boundaries.
Combines IT and data management expertise.
He / she develops algorithms to apply to external and internal data to predict customer needs and / or developments in markets, industries and the wider financial landscape.
Linking pin and liaison towards the Data Engineers
Problem Solving
Should be comfortable in solving Wholesale Banking domain analytical solution within AI/ML platform
Decision Making Authority & Responsibility
Knowledge, Skills and Experience
Master's or Ph.
D.
in statistics, mathematics, or computer science
Experience using statistical computer languages such as R, Python, SQL, etc.
Experience in statistical and data mining techniques, including generalized linear model/regression, random forest, boosting, trees, text mining, social network analysis
Experience working with and creating data architectures
Knowledge of machine learning techniques such as clustering, decision tree learning, and artificial neural networks
Knowledge of advanced statistical techniques and concepts, including regression, properties of distributions, and statistical tests
6+ years of experience manipulating data sets and building statistical models
Experience using web services:
Azure AI/ML , Redshift, S3, Spark, DigitalOcean, etc.
Experience analyzing data from third-party providers, including Google Analytics, Site Catalyst, Core metrics, AdWords, Crimson Hexagon, Facebook Insights, etc.
Experience with distributed data/computing tools:
Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
Experience visualizing/presenting data for stakeholders using: Periscope, Business Objects, D3, ggplot, etc
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