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
Requirements:
Bachelor’s or advanced degree in Computer Science, Statistics, Mathematics, or related field; 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
Text:
VP/Data Science Lead Analyst 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 Bachelor’s or advanced degree in Computer Science, Statistics, Mathematics, or related field; 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
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