Job Location: Bangalore/Bengaluru
Roles and 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
LOOKING FOR CANDIDATE WHO CAN JOIN US IMMEDIAETLY/ SERVING NOTICE PERIOD
- Should be comfortable in solving Wholesale Banking domain analytical solution within AI/ML platform
Knowledge, Skills and Experience•
Masters or Ph.D. in statistics, mathematics, or computer science • Experience usingstatistical computer languagessuch 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, includingregression, properties of distributions, and statistical tests • 6+ years of experiencemanipulating data setsand 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 distributeddata/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc. • Experience visualizing/presenting data for stakeholders using: Periscope, Business Objects, D3, ggplot, etc.