Data Scientist - Senior

Role Overview: At EY, you'll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we're counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. Key Responsibilities: - Develop customer-centric solutions with recommended data model and business intelligence (BI) technologies. - Create repeatable, interpretable, dynamic, and scalable statistical models that are seamlessly incorporated into analytic data products, ability to discover correlations between variables and generate predictions/forecasts of data-driven decisions. - Extract, transform, and load data from one data source (e.g., Databricks) into a single, consistent data source for data modelling and workflow orchestration purposes (i.e., representations of data flows and relationships). - Advocate and educate on the value of data-driven decision making with focus on how and why of solving problems. - Oversee forecasting models that process and analyze large quantities of data to identify key trends and business insights. - Review and refine data visualizations that are detailed, clear, multi-faceted, and user-focused to effectively communicate data insights throughout a narrative. Qualification Required: - Bachelor's degree in Data Science, Computer Science, Statistics, or related field - At least 3-5 years of experience of data mining/data analysis methods and tools, building and implementing models, and creating/running simulations - Familiarity with AI libraries and frameworks - Experience and proficiency in applied statistical modeling (e.g., clustering, segmentation, multivariate, regression, etc.) - Demonstrated understanding and experience using: - Data Engineering Programming Languages (i.e., Python, Pyspark) - Distributed Data Technologies (e.g., Spark, Hadoop, H20.ia, Cloud AI platforms) - Data Visualization tools (e.g., Tableau, R Shiny, Plotly) - Databricks/ETL - Statistical Model Packages (MLib/SciKit-Learn, Statsmodels) - GitHub - Excel - Creating new features by merging and transforming disparate internal & external data sets - Strong organizational skills with the ability to manage multiple projects simultaneously and operate as a leading member across globally distributed teams to deliver high-quality services and solutions - Processes proficiency in code programming languages (e.g., SQL, Python, Pyspark, AWS services) to design, maintain, and optimize data architecture/pipelines that fit business goals - Excellent written and verbal communication skills, including storytelling and interacting effectively with multifunctional teams and other strategic partners - Demonstrated knowledge of relevant industry trends and standards - Strong problem-solving and troubleshooting skills - Ability to work in a fast-paced environment and adapt to changing business priorities Note: Any additional details of the company were not present in the provided job description.,