Data Scientist

Data Scientist

Our 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 Science
• Significant 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 optimization
  • Analytics 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 documentation
• Proven ability to drive P&L impact through analytics
• Exceptional 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.