Data Scientist

Data ScientistOur client is looking for an intelligent, proactive, and results-driven Data Scientist to join our team. In this role, you'll work closely with the Financial Planning, Analysis & Performance Optimization Department and partner directly with IT to transform raw data into actionable strategies. With minimal travel required, you'll focus on leveraging advanced analytics to optimize processes, improve decision-making, and deliver measurable value. If you're a go-getter with a passion for solving complex problems using cutting-edge tools, we want to hear from you!Responsibilities:Data Analysis & Insights Analyze large datasets to identify trends, inefficiencies, and opportunities for performance improvement.Provide actionable recommendations to optimize operational and financial performance.Model Development & Deployment Develop and deploy predictive models and machine learning algorithms to support business objectives.Leverage advanced analytics platforms, such as Databricks, for scalable data processing.Data Integration Collaborate with IT and cross-functional teams to integrate data solutions into existing systems and workflows.Reporting & Visualization Design and maintain dashboards and reporting insights to stakeholders.Data/AI Strategy & Roadmap Identify and develop future AI use cases across the organization, driving innovation and helping shape the company's long-term Data Science and AI strategy.Stay current with industry trends and emerging technologies to continually enhance our data capabilities.Skills & Qualifications:Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.2-4 years of relevant industry work experience in Data ScienceSignificant relevant experience building and deploying Data Science solutions. Relevant topics include customer segmentation/clustering, pricing, optimization, and experimentation.Deep technical and data science expertise, with demonstrated experience in one or more of the following areas: Analytical methods: statistical modeling (e.g., linear regression, GLMs, time series), supervised machine learning (e.g., random forests), design of experiments, segmentation/clustering methods, mixed-integer linear optimizationAnalytics tools: Data wrangling (e.g. SQL), Versioning (e.g. Git), Data Modeling (e.g. python), Data processing frameworks (e.g. Spark/PySpark), Data visualization (e.g. Tableau)Data management environments: Analytics platforms (e.g. Databricks), data pipeline development (e.g. AWS Glue) a plus.Experience building in-production models, including associated scripting, error handling and documentationProven ability to drive P&L impact through analyticsExceptional problem-solving skills and a proactive, self-starter mindset.Ability to communicate complex technical concepts to non-technical stakeholders.Strong collaboration skills to work effectively with IT and other departments.Bonus: Familiarity with Pigment or similar business planning tools.