Senior 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!

• Data Analysis & Insights
• Analyze large datasets to identify trends, inefficiencies, and opportunities for performance improvement.
• Provide actionable recommendations to optimize operational and financial performance.
• 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.
• Design and maintain dashboards and reporting insights to stakeholders.
• 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

• Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
• 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)
• 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.

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