Lead Data Scientist

The Spec Analytics Intmd Analyst is a developing professional role. Deals with most problems independently and has some latitude to solve complex problems. Integrates in-depth specialty area knowledge with a solid understanding of industry standards and practices. Good understanding of how the team and area integrate with others in accomplishing the objectives of the sub function/ job family. Applies analytical thinking and knowledge of data analysis tools and methodologies. Requires attention to detail when making judgments and recommendations based on the analysis of factual information. Typically deals with variable issues with potentially broader business impact. Applies professional judgment when interpreting data and results. Breaks down information in a systematic and communicable manner. Developed communication and diplomacy skills are required in order to exchange potentially complex/sensitive information. Moderate but direct impact through close contact with the businesses' core activities. Quality and timeliness of service provided will affect the effectiveness of own team and other closely related teams.

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 (e.g. 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
• Specialization in marketing, risk, digital and AML fields possible
• 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

Experience:

• Bachelor’s Degree with 5-6 years of experience in data analytics, or Masters Degree with 4-6 years of experience in data analytics, or a PhD in a relevant subject.
• Must have substantial experience in:

oIdentifying and resolving business problems (around sales/marketing strategy optimization, pricing optimization, client experience, cross-sell and retention) preferably in the financial services industry (not must)

oUtilizing text data to derive business value by leveraging different NLP techniques (mid to expert level prior experience is a must)

oLeveraging and developing analytical tools and methods to identify patterns, trends and outliers in data

oHands on building build AI / ML classification and regression model from scratch

oExperience of working with Tech (Data Engineering) Teams to implement CI / CD pipeline and deploy / maintain models in production environment.

oApplying Predictive Modeling techniques for a wide range of business problems

oWorking with data from different sources, with different complexities, both structured and unstructured

• Good to have:

oExperience working with data from different sources and of different complexity

oPrior working experience in Customer experience domain (Analysis involving deep dive into CSAT, NPS, Survey feedbacks etc.)

Skills:

Analytical Skills:

• • Strong logical reasoning and problem solving ability
  • Proficient in converting business problems into analytical tasks, and analytical findings into business insights
  • 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:

• • Expert knowledge in Python, PySpark and related tools
  • Experience in Hive
  • Proficient in MS Excel, PowerPoint
  • Good to have:

oExperience with PySpark

oExperience with Tableau