Job Description
Description
:
The Spec Analytics Analyst is a developing professional role. Applies specialty area knowledge in monitoring, assessing, analyzing and/or evaluating processes and data. Identifies policy gaps and formulates policies. Interprets data and makes recommendations. Researches and interprets factual information. Identifies inconsistencies in data or results, defines business issues and formulates recommendations on policies, procedures or practices. Integrates established disciplinary knowledge within own specialty area with basic understanding of related industry practices. Good understanding of how the team interacts with others in accomplishing the objectives of the area. Develops working knowledge of industry practices and standards. Limited but direct impact on the business through the quality of the tasks/services provided. Impact of the job holder is restricted to own team.
Responsibilities:
Incumbents work with large and complex data sets (both internal and external data) to evaluate, recommend, and support the implementation of business strategies Identifies and compiles data sets using a variety of tools ( SQL, Access) to help predict, improve, and measure the success of key business to business outcomes Responsible for documenting data requirements, data collection / processing / cleaning, and exploratory data analysis; which may include utilizing statistical models / algorithms and data visualization techniques Incumbents in this role may often be referred to as Data Scientists Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency. Technical Skills:
Hands-on Experience in Python, SQL & Machine Learning (ML) is a must. Experience with PySpark, Natural Language Processing (NLP), Large Language Models (LLM/Gen AI), and prompt engineering is preferred. Writing clean, efficient, and well-documented code according to design specifications and coding standards. Utilizing version control systems (, Git) to manage code changes, collaborate with team members, and maintain code history. Configuring and maintaining automated build processes (, using Jenkins) to compile code, run unit tests, and create deployable artifacts. Ability to execute the code testing in Dev & UAT environments Automate deployment pipelines, follow release procedures, verify post-deployment, and troubleshoot production issues, if any. Understand dependencies, design/consume APIs, ensure data flow integrity, resolve integration issues, and maintain architectural awareness. Capability to validate/maintain deployed models in production Candidates with a background in Customer Experience (CX) analytics is preferred. Exposure to Credit card business is a strong plus for this position. Familiarity with the Software Development Life Cycle (SDLC) is preferred. Prior experience of Sprints deployment cycle is preferred.
Qualifications:
Bachelor’s Degree with atleast 3 years of working experience OR Master’s Degree with 2 years of working experience. Possess analytic ability and problem solving skills Working experience in a quantitative field Excellent communication and interpersonal skills, be organized, detail oriented, and adaptive to matrix work environment Ability to build partnerships with cross-functional teams
Education:
Bachelors/University degree in Computer Science Engg. / IT is preferred. ------------------------------------------------------
Job Family Group:
Decision Management
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Job Family:
Specialized Analytics (Data Science/Computational Statistics)
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Time Type:
Full time
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Most Relevant Skills
Please see the requirements listed above.
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Other Relevant Skills
Machine Learning (ML), Python (Programming Language).
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