Sr Data scientist

at Fragma Data Systems

Sr Data scientist

Fragma Data Systems

Company

Home

Sr Data scientist

at Fragma Data Systems

Posted by Sandhya JD

5 - 10 yrs

₹15L - ₹40L / yr

Remote only

Skills

Machine Learning (ML)

Data Science

Natural Language Processing (NLP)

Computer Vision

recommendation algorithm

Job Overview:

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 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.

Primary Responsibilities

 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 predictive modeling 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

Desired Experience

6 Years - 10 Years

Function

Analytics

Desired Skills

Should be comfortable in solving Wholesale Banking domain analytical solution within AI/ML platform

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, Coremetrics, 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.

Job Overview:

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 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.

Primary Responsibilities

 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 predictive modeling 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

 Linking pin and liaison towards the Data Engineers

Desired Experience

6 Years - 10 Years

Function

Analytics

Desired Skills

Should be comfortable in solving Wholesale Banking domain analytical solution within AI/ML platform

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, Coremetrics, 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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About Fragma Data Systems

Founded :

2015

Type :

Products & Services

Size :

100-1000

Stage :

Profitable

About

Fragma is a leading Big data, AI and Advanced analytics company provideing services global clients.

Mallikarjun Degul

Sandhya JD

Varun Reddy

Priyanka U

Simpy kumari

Minakshi Kumari

Latha Yuvaraj

Vamsikrishna G

Company social profiles

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Algorithms

C++

The platform engineering team designs builds and owns the systems to support the various applications, products, and services. We are a team of highly motivated individuals with a passion for solving large complex problems. We value an aptitude for research and a passion for learning. Together we are building one of the largest distributed computing platforms in the country. As a part of the engineering team you will be: • building highly-scalable and secure payments platform • primary owners of one or more components of the platform and will drive innovation in your area of ownership • working with various product teams gathering requirements and adding capabilities • working with some of the smartest people in the industry and will have ample opportunity to learn and grow • using cutting-edge cryptography to secure payments beyond industry standards. • deriving actionable insights by mining TBs of data. • building low-level infrastructure that aims to push the boundaries of network performance. • participating actively in recruitment and nurturing of engineers as awesome as you. What are we looking for ? Review and influence new evolving design, architecture, standards and methods with stability, maintainability and scale in mind Identify patterns and provide solutions to class of problems Research, evaluate and socialize new tools, technologies, and techniques to improve the value of the system Be able to multi-task, prioritize and handle dependencies with minimal oversight. From a technology perspective, you should have knowledge and/or experience in a reasonably sized subset of the following ( the more, the merrier!! ) Worked on one or more large scale java applications. Good understanding of nuances of distributed systems, scalability, and availability. Good knowledge of one or more relational and NoSQL databases and transactions. Shrewd focus on latency and throughput of services. In-depth understanding of concurrency, synchronization, NIO, memory allocation and GC. Experience with IaaS clouds like AWS/Google Cloud, Azure, OpenStack etc.. Experience in working with Message Brokers and Application Containers Great ability to mentor and train other team members. Plus Points: Clear understanding of the CAP theorem and its implications for real-world distributed systems. “Call me maybe” is more than just a song for you. You have studied distributed systems like Dynamo, HBase, various messaging and queuing systems and understand nuances of Time, Clocks, and Ordering of Events, rate control, load distribution. You can smell fraud, transaction risks and abuse a mile away.

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