Few notables among the multiple areas that we work in:
- Cutting Edge Data, Analytical, Modelling Tools and Platforms –Build, Setup and adopt cutting edge technologies and technology platforms to improve analysts efficiency, time to market and controls.
- Opportunity sizing: Help the business with sizing the impact of various regulatory / market / business / strategic changes to the portfolio
- Process Efficacy: Periodically review existing process and identify potential ways to streamline the process
- Business Intelligence Tools: Deploy existing reports to other advanced reporting platforms
- Data obsession –Own data platforms to streamline data creation, management and maintenance to govern the organization data and make it available in most compliant manner to analysts in conjunction with our technology partners.
- Technology leadership– Manage team members and technology partners and their deliverables to fulfill analytics business projects
- Client Obsession– Create client centric analytic solution to business problems. Individual should be able to have a holistic view of multiple businesses and develop analytics solutions accordingly.
- Analytic Project Execution– Own and deliver multiple and complex analytic projects. This would require an understanding of business context, conversion of business problems to formulate analytical methodology, identifying trends and patterns with data
- Stakeholder Management: Experience in stakeholder management across various functions and regions.
- Presentation Skills: Delivering high class presentations to share the thoughts, the solutions or the problem statement to business stakeholders and senior management
- Project Management– Shouldhaveskillset to manage project in terms of creating project plan, assigning responsibilities,
Skillset you should possess
The most important skill that our analyst should possess is their love for data and their eagerness for new challenges & solving new problems. Apart from these, they should also have the following skillset
Basic Qualifications
- Degree in computer science, engineering, mathematics, operations research or other quantitative field and strong relevant industry experience
- Preferred masters in above fields.
- 2-4 years of industry experience in the field of ML/data science with using variety of ML techniques such as supervised, unsupervised, deep learning and NLP.
- Demonstrated strong coding and programming abilities for Python, SQL and Linux
- Understanding of statistics and probabilities
- Experience with data munging, manipulating large datasets, data engineering and visualization
- Has the ability to analyze and interpret modeling results
- Experience with ML open source tools and APIs like Scikit-Learn, Tensor flow/ keras, Numpy, scipy, pandas, matplotlib, just to name a few.
- Experience with NLP open source tools like NLTK, Gensim, spaCy, TextBlob, etc.
- Experience with Big data technologies like Hive, PySpark, etc.
- Experience with LLM models , Transformer, BERT, GPT ad ability to train /retrain new LLM model.
- Good communication skills with ability to write proper documentation, and team player
- Experience/understandingcloud platform like AWS is a plus
- Ability to work on projects without continuous supervision in individual capacity
- Experience in working on Credit Cards and Retail Banking products is a plus
- Control orientated and Risk awareness.
Other details
- Location: Bangalore, India
- Employment: Full Time
- Industry: Credit Cards, Financial Services, Banking, Marketing Analytics , Retail Banking
Decision ManagementSpecialized Analytics (Data Science/Computational Statistics)
Time Type:
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