Citi Group Data Science Lead Analyst C13 

India 

899152647

Enterprise Excellence (EE) is a group within the Operations and Technology (O&T) organization that designs solutions to enhance transparency, empowers Operations and Functions to improve processes and evolves the organization through continuous improvement and simplification. The organization is responsible for defining, deploying and driving alignment and progress against a firm-wide framework that reduces operational risk, standardizes workforce optimization and improves process health.

Responsibilities:

• Lead end-to-end data science Enterprise Excellence projects, from problem formulation to model deployment to address Citi Line of Business challenges and opportunities.
• Collaborate closely with cross-functional teams, including technology, re-engineering, product management, and business stakeholders, to define project requirements and deliverables.
• Apply advanced statistical and machine learning techniques to analyze large, complex datasets and extract actionable insights.
• Apply mathematical, problem-solving, and coding skills to manage big data, extracting valuable insights.
• Develop predictive models, algorithms, and data-driven solutions to optimize business process, improve product performance, and drive strategic decision-making.
• Design and conduct experiments, tests, and casual inference analysis to evaluate the effectiveness of interventions and initiatives.
• Mentor and coach team members, providing guidance on best practices, methodologies, and tools in data science and machine learning.
• Stay-up-to-date with the latest developments in data science, machine learning, and related fields, and evaluate emerging technologies for potential adoption.

Qualifications:

• 6 to 8 years of relevant experience, with 4+ years of professional experience in data science, with strong foundation in statistical analysis, machine learning, and data visualization
• Proficiency in programing languages such as Python, R, or Scala, and familiarity with libraries/frameworks such as TensorFlow, PyTorch, scikit-learn, or spark
• Solid understanding of experimental design, hypothesis testing, and casual inference methods
• Experience with SQL and relational databases for data manipulation and querying
• Proficiency with data mining, mathematics, and statistical analysis
• Excellent communication and collaboration skills, with the ability to explain complex technical concepts to non-technical stakeholders
• Strong problem-solving and critical-thinking abilities, with a demonstrated ability to tackle open-ended problems and drive projects to completion
• Advanced experience in pattern recognition and predictive modeling
• Ability to work effectively in a dynamic, research-oriented group that has several concurrent projects
• Experience working with large-scale distributed computing frameworks and cloud platforms (e.g, AWS)
• Knowledge of software engineering best practices, including version control, testing and deployment pipelines
• Familiarity with natural language generation (NLG), natural language processing (NLP), computer vision, or other specialized areas of machine learning

Bachelor’s or advanced degree in Computer Science, Statistics, Mathematics, or related field

This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.

Time Type:

View the " " poster. View the .

View the .

View the