Data Science Specialist
3 weeks ago
Role: Data Science Lead Role(Hybrid)
Location:Chicago , IL(locally available or near by to Chicago , IL)
The Data Science Lead provides strategic direction for data science initiatives, overseeing projects that drive business value through advanced analytics. This role involves managing teams, aligning projects with business goals, and ensuring successful delivery of data-driven solutions.
Qualifications:
· Bachelor's or Master's Degree in Data Science, Computer Science, Statistics, or related field.
· Preferred: PhD in a quantitative field.
Experience:
· 8-10+ years of experience in data science or analytics.
· 3-5 years in a leadership role managing data science teams.
· Experience in the QSR, retail, or related industries is highly desirable.
Desired Skills:
· Understanding of customer behavior analytics, loyalty programs, and menu optimization.
· Experience in building models for customer segmentation, personalized marketing, and promotional effectiveness.
· Proven experience in developing predictive models for sales, inventory management, and demand forecasting across multiple locations.
· Experience with process optimization, staff scheduling, and supply chain logistics to improve efficiency and reduce costs.
Leadership & Strategy:
o Strong leadership and team management abilities.
o Experience developing and executing data science roadmaps.
o Strategic thinking and business acumen.
o Ability to identify opportunities where data science can deliver value.
Technical Expertise:
o Proficiency in statistical modeling, machine learning, and deep learning.
o Knowledge of programming languages (Python, R, SQL).
o Familiarity with big data technologies (Spark, Hadoop).
o Experience with cloud platforms (Azure, AWS, GCP).
Communication & Storytelling:
o Ability to translate technical results into business insights.
o Strong communication and presentation skills for stakeholder engagement.
Project Management:
o Agile methodology knowledge (Scrum, Kanban).
o Experience in managing end-to-end project lifecycles.
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