Data Scientist -Bengaluru

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TTS Analytics C10

What do we do?

The TTS Analytics team provides analytical insights to the Product, Pricing, Client Experience and Sales functions within the global Treasury & Trade Services business. The team works on business problems focused on driving acquisitions, cross-sell, revenue growth & improvements in client experience.
The team extracts relevant insights, identifies business opportunities, converts business problems into analytical frameworks, uses big data tools and machine learning algorithms to build predictive models & other solutions, and designs go-to-market strategies for a huge variety of business problems.

Role Description

The role will be Spec Analytics Analyst 2 (C10) in the TTS Analytics team
The role will report to the AVP leading the team
The role will involve working on multiple analyses through the year on business problems across the client life cycle – acquisition, engagement, client experience and retention – for the TTS business
This will involve leveraging multiple analytical approaches, tools and techniques, working on multiple data sources (client profile & engagement data, transactions & revenue data, digital data, unstructured data like call transcripts etc.) to provide data driven insights to business and functional stakeholders

Qualifications

Experience:

Bachelor’s Degree with 3+ years of experience in data analytics, or Master’s Degree with 2+ years of experience in data analytics, or PhD.
Must have:

In-depth knowledge of machine learning is must across variety of algorithms, like regression, tree based methods etc.
Experience across different analytical methods like hypothesis testing, segmentation, time series forecasting, test vs. control comparison etc.
Predictive modeling using Machine Learning
Experience with unstructured data analysis, e.g. call transcripts, using Natural language Processing (NLP)/ Text Mining

Good to have:

Experience in financial services
Deep learning and Gen AI exposure
Proficiency in Gen AI tools like Copilot etc.

Skills:

Analytical Skills:

Proficient in data science and machine learning concepts and must have experience in implementing the knowledge in actual industry projects
Proficient in formulating analytical methodology, identifying trends and patterns with data
Has the ability to work hands-on to retrieve and manipulate data from big data environments

Tools and Platforms:

Proficient in Python/R, SQL
Experience in Hive
Proficient in MS Excel, PowerPoint
Good to have:

Experience with PySpark
Experience with Tableau

Soft Skills:

Strong analytical and problem-solving skills
Excellent communication and interpersonal skills
Be organized, detail oriented, and adaptive to matrix work environment

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