Citigroup is a global financial services firm that offers a wide range of financial products and services to individuals, businesses, governments, and institutions. We strive to create the best solutions for our clients by working as one, collaborative team in over 160 countries and jurisdictions. Citi Data, Digital, and Innovation seeks an experienced Senior Vice President Data Scientist to join our Boston team. This position requires the candidate to have a solid machine learning (ML) foundation. In addition, we require exceptional soft skills such as communication, leadership, and problem-solving. As a Citigroup Data Scientist, you can shape our organization’s future by leveraging data-driven insights to drive innovation and growth. (2) Core Responsibilities As a Senior Vice President Data Scientist, your core responsibilities will include: Develop and implement advanced ML models to solve complex business problems and generate valuable decision-useful results Collaborate with cross-functional teams to define data requirements, identify data sources, and collect and preprocess data for model development Evaluate the performance of existing models and recommend improvements or new approaches to enhance their effectiveness Stay up-to-date with the latest research and advancements in ML to ensure the adoption of best practices and state-of-the-art solutions Present complex findings and insights to technical and non-technical stakeholders clearly and concisely, driving data-driven decision-making across the organization Actively participate in the development and execution of data-driven strategies to support the organization’s goals and objectives (3) Qualifications To be considered for the SVP Data Scientist position, candidates must possess the following qualifications: A minimum of 5-7 years of relevant data science experience, focusing on ML Post-graduate degree in Computer Science, Data Science, Statistics, or a related field is preferred; a CFA charter is a plus Strong programming skills in Python, R, or other relevant languages Knowledge of various ML algorithms (e.g., supervised, unsupervised, and reinforcement learning), feature engineering and selection techniques, and model evaluation and validation Experience with ML frameworks such as TensorFlow, PyTorch, and scikit-learn Excellent communication and presentation skills, with the ability to explain complex concepts to both technical and non-technical audiences Strong leadership and teamwork skills, with the ability to collaborate effectively across various teams and disciplines A proven track record of problem-solving, adaptability, and creativity in addressing complex challenges Citigroup is an equal-opportunity employer and is committed to creating a diverse and inclusive workplace. Therefore, we encourage applications from all qualified candidates, regardless of race, color, religion, gender, sexual orientation, national origin, age, disability, or veteran status. ————————————————- Job Family Group: Product Management and Development ————————————————- Job Family: Digital Product Management —————————————————— Time Type: Full time —————————————————— Primary Location: Boston Massachusetts United States —————————————————— Primary Location Salary Range: $182,400.00 – $273,600.00 —————————————————— Citi is an equal opportunity and affirmative action employer. Qualified applicants will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. Citigroup Inc. and its subsidiaries (“Citi”) invite all qualified interested applicants to apply for career opportunities. If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi . View the ” EEO is the Law ” poster. View the EEO is the Law Supplement . View the EEO Policy Statement . View the Pay Transparency Posting
scikit-learn feature-engineering statistics Problem-solving Python R model-validation Communication unsupervised-learning reinforcement-learning Machine Learning TensorFlow supervised-learning Leadership PyTorch