Job Description

The Specialized Analytics Ld Analyst is a strategic professional who stays abreast of developments within own field and contributes to directional strategy by considering their application in own job and the business. Recognized technical authority for an area within the business. Requires basic commercial awareness. There are typically multiple people within the business that provide the same level of subject matter expertise. Developed communication and diplomacy skills are required in order to guide, influence and convince others, in particular colleagues in other areas and occasional external customers. Significant impact on the area through complex deliverables. Provides advice and counsel related to the technology or operations of the business. Work impacts an entire area, which eventually affects the overall performance and effectiveness of the sub-function/job family.

Responsibilities:

• Performing data extraction, manipulation and processing, explore new data sources and integrate into pipeline
• Effectively using programming languages and tools (e.g., Python, PySpark, SAS, SQL, Excel)
• Normalize data to perform design of experiments; analyze and finalise data in required structure; design appropriate dashboards
• prompt engineering and large language models, Cypher Query, User Stories based few-shot modeling, Ground Truth verification, RAG, Knowledge Graphs, Guardrail models
• Incumbents in this role may often be referred to as Data Scientists
• Clustering and segmentation
• Classification and regression techniques
• Ensemble modelling/advanced machine learning models, Natural Language Processing
• P&L quantification of financial impact of models implemented in the market through CRM efforts
• 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.

Qualifications:

• 8 - 14 years of experience (We have multiple roles at AVP/VP level)
• Experience in a quantitative field, working hands-on in Data Analysis, Statistics, Machine Learning and Feature Engineering
• Must have Demonstrated ability in AI: Gen AI: prompt engineering and large language models, Cypher Query, User Stories based few-shot modelling, Ground Truth verification, RAG, Knowledge Graphs, Guardrail models, Optical Charter Recognition (OCR)/ computer vision, Deep learning and neural networks
• Excellent analytic ability and problem solving skills
• Proficient in Microsoft Office including excellent MS Excel skills and Microsoft Powerpoint to develop analytic presentations
• Excellent communication and interpersonal skills, be organized, detail oriented, and adaptive to matrix work environment
• Stakeholder Management: Stakeholder mapping; identifying who to engage for responsibilities and actions; Interpersonal ability; building relationships virtually ; Influencing, negotiation, alignment on priorities/incentives and conflict resolution with stakeholders; stakeholder communication
• Project Management: Prioritization; resource planning, timelines management and escalations, governance on projects; project status communications; running steercos; Navigating through constantly evolving timelines and project scope including
• Data Engineering: Manipulating data in a distributed system natively (Hadoop Clusters) as well as on cloud (AWS Clusters). MLOPS platforms like 'MLflow', 'AWS Sagemaker' and 'Vertex AI’. Front end integration: Python frameworks like Streamlit and Flask or R frameworks like R Shiny etc., JavaScript (preferred but not mandatory), bootstrap (preferred but not mandatory) and CSS (preferred but not mandatory)

Education:

• Bachelors/University degree, Master’s degree preferred

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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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Qualified applicants will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

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