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Citi
Citi
H1B Visa SponsorBankingFinanceFintech
Citi is a global banking and financial services company serving consumers, corporations, governments, and institutions. Its offerings span consumer banking, credit cards, wealth management, corporate banking, and investment banking, supported by operations in more than 100 countries. As a large international finance organization, Citi brings together teams working across banking, financial services, and fintech.
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Machine Learning Engineer (Python, SQL) – Citi, Pune Hybrid

Join Citi’s global Treasury & Trade Services business to build production machine learning, Python, SQL, and Generative AI solutions. The role combines scalable data pipelines, advanced analytics, and measurable business impact.

INIndiaHybridFull-timeMiddleSeniorEnglish RequiredBackend EngineerSoftware Engineer
ETLPySparkPythonScikit-LearnSQL

Description

  • Examine large, complex datasets to uncover patterns, trends, risks, and opportunities.
  • Create analytical frameworks for client experience, pricing, acquisition, cross-selling, and retention initiatives.
  • Convert unclear business needs into structured data science and analytical solutions.
  • Design, develop, validate, and deploy machine learning models.
  • Deliver models that create measurable business value and inform decisions.
  • Build and improve Generative AI applications.
  • Design, develop, and maintain scalable ETL/ELT pipelines and data workflows for analytics and AI initiatives.
  • Work with data engineering teams to strengthen data quality, lineage, governance, and platform scalability.
  • Coordinate with business, product, operations, technology, and data teams to prioritize and deliver high-impact initiatives.
  • Communicate analytical findings, model results, and recommendations to technical and non-technical audiences, including senior leaders.
  • Use data science, machine learning, and Generative AI methods to address complex business challenges with scalable analytical solutions.

Requirements

  • Bachelor’s or master’s degree in computer science, data science, statistics, engineering, mathematics, or a related quantitative field.
  • Three to five years of experience in data science, machine learning, advanced analytics, or a related discipline.
  • Experience in banking, financial services, or another highly regulated industry is preferred.
  • Proven experience deploying production-grade machine learning or AI solutions.
  • Strong Python proficiency is required.
  • Advanced SQL skills.
  • Experience with PySpark and large-scale data processing.
  • Practical experience with supervised and unsupervised learning methods.
  • Practical experience with statistical modeling and hypothesis testing.
  • Practical experience designing experiments and conducting A/B tests.
  • Experience with Scikit-learn.
  • Experience with XGBoost and/or LightGBM.
  • Experience developing ETL/ELT pipelines.
  • Experience with data modeling.
  • Experience implementing CI/CD for machine learning workloads.
  • Experience with model monitoring and performance management.
  • Experience with version control and deployment frameworks.
  • Strong analytical and problem-solving capabilities.
  • Ability to identify trends, patterns, and actionable insights in structured and unstructured data.
  • Ability to develop analytical methodologies and independently conduct complex analyses.
  • Strong written and verbal communication skills.
  • Ability to influence stakeholders with data-driven recommendations.
  • Comfort working in cross-functional, matrixed organizations.
  • Strong attention to detail and organizational ability.
  • Ability to manage competing priorities and deliver in a fast-paced environment.
  • Strong accountability and ownership of outcomes.

Benefits

  • Equal opportunity employment.
  • Reasonable accommodation is available for persons with disabilities.

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