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Senior Data Scientist role at Citi, focusing on advanced analytics and machine learning.
Join a global team and lead data‑driven solutions.
Discover your future at Citi
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Job Overview
We are seeking an experienced and highly motivated Senior Data Scientist to join our dynamic team. The successful candidate will be instrumental in developing and deploying advanced analytical models, extracting meaningful insights from complex datasets, and contributing to data-driven decision-making across the organization. This role requires a strong background in statistical modeling, machine learning, and programming, coupled with excellent communication skills to translate complex findings into actionable strategies.
Key Responsibilities
- Model Development & Deployment: Design, develop, and implement advanced machine learning models, statistical analyses, and predictive algorithms to solve complex business problems. Translate prototypes into production-ready solutions, ensuring scalability, efficiency, and reliability.
- Data Analysis & Insight Generation: Conduct in-depth exploratory data analysis to identify trends, patterns, and anomalies. Extract actionable insights from large, diverse datasets and communicate findings effectively to technical and non-technical stakeholders.
- Problem Framing & Solution Design: Collaborate with business stakeholders to understand key challenges, define problem statements, and formulate data-driven solutions. Translate business requirements into technical specifications for data science projects.
- Algorithm & Technique Expertise: Apply a wide range of machine learning techniques (e.g., supervised, unsupervised, reinforcement learning), statistical methods, and optimization algorithms. Stay abreast of new research and advancements in the field.
- Data Governance & Quality: Work closely with data engineering teams to ensure data quality, accessibility, and appropriate governance for analytical purposes.
- Mentorship & Leadership: Provide technical guidance and mentorship to junior data scientists. Contribute to the development of best practices, coding standards, and model documentation within the team.
- Cross-Functional Collaboration: Partner with product managers, engineers, and other teams to integrate data science solutions into products and operations.
- Experimentation & A/B Testing: Design and analyze A/B tests and other experiments to evaluate the impact of new features, models, and business strategies.
Qualifications
5+ years of professional experience in data science, machine learning, or a related analytical role.
Proficiency in programming languages such as Python (with libraries like scikit-learn, TensorFlow, PyTorch, Pandas, NumPy) or R.
Strong expertise in statistical modeling, hypothesis testing, experimental design, and causal inference.
Demonstrated experience with various machine learning algorithms (e.g., regression, classification, clustering, deep learning, NLP).
Solid understanding of data structures, algorithms, and software development best practices.
Experience with SQL and working with large-scale relational and non-relational databases.
Familiarity with big data technologies (e.g., Spark, Hadoop) and cloud platforms (e.g., AWS, Azure, GCP).
Excellent communication and presentation skills, with the ability to explain complex analytical concepts to diverse audiences.
Proven ability to work independently and collaboratively in a fast-paced environment.
Preferred Qualifications
Experience with MLOps practices and tools for deploying, monitoring, and maintaining machine learning models in production.
Publications in relevant conferences or journals.
Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn).
Familiarity with Agile development methodologies.
Job Family Group: Decision Management
Job Family: Specialized Analytics (Data Science/Computational Statistics)
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.
Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.
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