Assistant Manager - AI & Data - EY Studio+

Job Description Roles & Responsibilities About the Role: We re seeking an experienced data scientists to deliver insights and act as the hands on modeling lead on client engagements. You will slice and dice data using various methods and create new visions for the future. You ll frame problems, engineer features, build and deploy models, and monitor them in production to support the customer value creation activities. You will ship models that run at scale, withstand audit, and clearly link to incremental business value. While mining, interpreting, and cleaning the data, you will be relied on to ask questions, connect the dots, and uncover hidden opportunities for realizing the data s full potential. The ideal candidate will have mathematical and statistical expertise, extensive programming experience in multiple languages along with natural curiosity and a creative mind. Core Responsibilities: Problem Framing & Target Definition: Translate commercial goals into modeling problems (e.g., churn, propensity to buy, uplift, LTV, survival/tenure) with clear success metrics and guardrails Identify relevant data sources to mine for client business needs, and collect large structured and unstructured datasets and variables Data Analysis: Serve as data strategist to identify and integrate new datasets and execute analytical experiments to help solve problems across various domains and industries Devise and utilize algorithms and models to mine data, perform data and error analysis to improve models, clean and validate data for uniformity and accuracy Analyze data for trends and patterns, and interpret data with clear objectives in mind Model Development: Create reproducible pipelines and a feature registry to calculate model inputs Develop and evaluate churn, cross/upsell propensity, uplift/treatment effect, LTV, ranking/NBA models and select algorithms fit for data, scale, and explainability Use clear control/holdouts, quantify precision vs. recall, calibration, and profit curves, simulate outcomes and set practical thresholds and simple policies (eligibility, suppressions, frequency caps) Operationalization: Implement analytical models in production by collaborating with software developers and machine-learning engineers Implement scoring and integrate outputs with client MarTech/decisioning for SMS, email, in app, IVR, and agent assist Set up monitoring (performance, drift, calibration, data quality), alerting, and retrain cadence with rollback criteria Governance, Risk & Explainability: Produce model cards, document features/exclusions, and run proportionate explainability/fairness checks for regulated contexts and maintain audit ready artifacts Enablement & Acceleration: Create templates, reusable code, and quick start notebooks, /coach client analysts on model usage and monitoring Contribute to practice POVs/case studies as needed What we look for Highly motivated individuals with excellent problem-solving skills and the ability to prioritize shifting workloads in a rapidly changing industry. An effective communicator, you ll be a confident team player that collaborates with people from various teams while looking to develop your career in a dynamic organization. Desired Candidate Profile 3 to 6 years of hands-on experience in applied data science with proficiency in data mining, mathematics, and statistical analysis Experience either in an in house data science role at a leading industry player or in a consulting company AI & Advanced Analytics team with multi industry exposure Structured problem solver with strong client facilitation skills and executive storytelling ability (able to translate technical findings into clear commercial recommendations) Advanced experience in pattern recognition and predictive modeling Ability to work with multiple programming languages and datamining tools Able to work effectively in a dynamic, research-oriented group that has several concurrent projects Bachelor s degree in the field of computer science is preferred (not mandatory) Technical Expertise: Data platforms: Azure Synapse/Databricks, Google BigQuery, Snowflake, or Amazon Redshift Languages: SQL, Python, R and SAS BI/Reporting (any): Power BI, Tableau Company Industry BankingFinancial ServicesBroking Department / Functional Area IT Software Keywords Assistant Manager - AI & Data - EY Studio+ Get real-time job updates only on our App