Data Scientist

Lead Data Scientist

As Lead Data Scientist, you will steer data-driven solutions for Spectrum Reach's advertising sales. You'll model, analyze, and interpret large datasets to drive actionable insights and measurable impact. You'll lead analytics lifecycles, mentor team members, and present findings to diverse audiences. This role blends technical leadership with strategic influence to elevate customer experiences and business outcomes. You will work across teams to scale analytics and innovate with AI/ML methods.

Compensation / Benefits

• comprehensive pay and benefits package
• focus on well-being at every life stage
• equal opportunity employer

Responsibilities

• Lead end-to-end analytics lifecycle for problem solving, from requirements to deployment
• Develop and validate predictive models and data-driven solutions for advertising sales
• Perform large-scale exploratory data analyses and establish data linkages
• Design modular analytics products and contribute to reusable codebases
• Interpret results for causal inferences and predictive effectiveness and translate into actionable recommendations
• Present findings to broad audiences and manage follow-ups and execution
• Teach techniques to BI, data, and analytics professionals and mentor junior team members
• Create project plans, monitor progress, and escalate issues as needed
• Support simplification of customer experience through analytics-driven improvements

Key requirements

• Proficiency in R and/or Python with relevant packages for advanced analytics and AI/ML
• Strong SQL skills and experience handling large data sets; data warehousing knowledge
• Experience with commercial cloud platforms (AWS, Azure, GCP)
• Solid understanding of ML model families (regression, classification, clustering, neural networks, LLMs)
• Experience with large-scale time series forecasting
• Advanced mathematical foundation (calculus, probability, statistics) and ability to learn new concepts
• Effective synthesis and presentation skills; ability to communicate with varied audiences
• Willingness to continuously expand skills and contribute to teaching others

• strong communication
• leadership and mentorship
• collaboration across cross-functional teams