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Data Analyst
2 weeks ago
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 Data/Information Mgt Analyst 2 (C10) in the TTS Analytics team
The role will report to the AVP/VP 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
The work involves setting up and optimizing data pipelines using big data technologies such as PySpark, Scala, and Hive. The role will also include working with SQL and NoSQL databases (e.g., MongoDB) to manage and retrieve data effectively.
The role requires designing and deploying interactive Tableau dashboards to visualize data insights and provide stakeholders with actionable information using features such as Tableau Prep Flows, Level of Detail (LOD) Expressions, Table Calculations etc.
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 enable data driven insights to business and functional stakeholders
Experience:
Bachelor's Degree with 4+ years of experience in data analytics, or Master's Degree with 2+ years of experience in data analytics
Must have:
Marketing analytics experience
Proficiency in designing and deploying Tableau dashboards
Strong experience in data engineering and building data pipelines
Experience with big data technologies such as PySpark, Scala, and Hive
Proficiency in SQL and experience with various database systems (e.g., MongoDB)
Good to have:
Experience in financial services
Experience across different analytical methods like hypothesis testing, segmentation, time series forecasting, test vs. control comparison etc.
Skills:
Analytical Skills:
Strong analytical and problem-solving skills related to data manipulation and pipeline optimization
Has the ability to work hands-on to retrieve and manipulate data from big data environments
Ability to design efficient data models and schemas
Tools and Platforms:
Proficient in Python/R, SQL
Experience in PySpark, Hive, and Scala
Strong knowledge of SQL and NoSQL databases such as MongoDB etc.
Proficiency with Tableau (designing and deploying advanced, interactive dashboards)
Proficient in MS Office Tools such Excel and PowerPoint
Soft Skills:
Strong analytical and problem-solving skills
Excellent communication and interpersonal skills
Be organized, detail oriented, and adaptive to matrix work environment
Job Family Group:
Decision Management
Job Family:
Data/Information Management
Time Type:
Full time
Most Relevant Skills
Please see the requirements listed above.
Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter.
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