Lead Data Scientist

Love’s•Oklahoma City, OK

16d

About The Position

The Lead Data Scientist is a hands-on analytics leader responsible for advancing marketing and customer analytics across Love’s convenience store network. This role blends deep technical expertise with people leadership, owning high-impact analytical initiatives that influence revenue growth, customer experience, and marketing effectiveness.

Requirements

BA/BS minimum, Masters preferred, in a relevant field, such as business analytics, mathematics, statistics, finance, economics, management information systems, computer science, engineering or other quantitative fields.
6+ years of experience preferred in retail, sales, marketing, data, IT, or operations with exposure to reporting and analytics
In-depth, hands-on knowledge of data science tools preferred
Proven experience with troubleshooting principles and issue resolution technique
6+ years of experience querying data from relational databases using SQL, using advanced algorithms, programming languages, or technologies in the development of technical analytics solutions or capabilities, and extracting insights from large databases, translating data and insights into actionable solutions and presenting findings
Competency using R, Python, or other similar statistical software to develop analytical solutions
Experience with data wrangling, data cleaning and prep
Proven ability to juggle multiple workstreams as needed
Data modelling and business analytics experience especially within the retail or marketing domain
Excel proficiency including simple formulas and pivot tables
Understanding of data warehouse principles and database structures
Data visualization skills and ability to present technical solutions to non-technical audience
1+ years of experience with mentoring or leading analytical projects
Natural curiosity that welcomes and embraces change and willingness to try new things
Excellent written, oral and interpersonal skills
Ability to devise an analytical approach to solving business problems
Capacity to explain and simplify complex analytics for a wide range of audiences
Work effectively within a team-oriented and collaborative environment
Keen attention to detail
Highly motivated self-starter
Must be authorized to work in the U.S. without sponsorship

Responsibilities

Develop deep understanding of Love’s business, including products, strategy, customers, and performance, and guide your team in aligning analytics initiatives with business priorities
Collaborate with Marketing and other business units to understand needs and design analytical approaches, then lead your team in implementing advanced analytics and machine learning solutions for key domains such as marketing and operations to deliver actionable insights
Contribute to the development of enterprise-wide analytics strategy and roadmap, representing the team’s perspective
Utilize statistical programming languages (R, Python, SAS) to manipulate data and extract insights from large datasets, ensuring team members follow best practices
Apply advanced statistical techniques (e.g., A/B testing) and machine learning methods (e.g., time series forecasting, clustering) to solve business problems
Supervise and develop a team of data scientists, analysts, and/or analytics engineers by setting goals, managing performance, providing feedback, and fostering a collaborative, high-performing environment
Promote best practices in data science methodologies, modeling, experimentation, documentation, and model governance across the team
Prioritize team workload and manage delivery timelines in alignment with strategic objectives
Identify gaps in measurement and data solutions and lead efforts to recommend and implement improvements that maximize analytics impact
Communicate complex insights clearly to stakeholders through presentations, reports, and visualizations, coaching team members on effective storytelling
Partner with data engineering to ensure scalable and robust data infrastructure that supports team objectives
Stay current with industry trends and emerging tools, introducing innovative techniques into the team’s practice