We are seeking a highly skilled Data Scientist with a strong background in operations research, mathematical programming, and enterprise data science solutions. This role is ideal for someone who thrives in a fast-paced, research-driven environment, can independently break down complex problems, and enjoys collaborating with a team of PhDs to build scalable data-driven solutions.

MUST-HAVE SKILLS:

• Scientific Programming & Optimization – Experience with SciPy, mathematical programming, and optimization techniques.
• Big Data & Cloud Expertise – Strong proficiency in Python, PySpark, and SQL, with experience in Databricks, AWS, or similar enterprise platforms.
• Problem-Solving & Ownership Mentality – Ability to break down complex problems, work autonomously, and execute tasks with minimal supervision.
• Effective Communication – Ability to present technical concepts in simple terms to business stakeholders and cross-functional teams.
• Enterprise Data Science Experience – Hands-on experience in retail operations, inventory management, or large-scale business solution.

NICE-TO-HAVE SKILLS:

• Experience with ML frameworks – TensorFlow, Scikit-learn, MLlib.
• Familiarity with CI/CD practices in enterprise data science projects.
• Experience in optimization, supply chain, or retail analytics.
  Job Type: Full-time

Benefits:

• Health insurance
• Paid time off
• Referral program
• Relocation assistance

Compensation Package:

• Bonus opportunities
• Yearly bonus

Schedule:

• 8 hour shift
• Day shift
• Monday to Friday

Experience:

• Pyspark: 4 years (Required)
• SciPy: 4 years (Required)
• Machine learning frameworks: 4 years (Required)
• Algorithms: 2 years (Required)
• SQL: 4 years (Required)

Work Location: Remot

• Develop and deploy operations research solutions with integrated machine learning and data science methodologies.
• Build enterprise-grade data science solutions, not just standalone models (e.g., Kaggle-style projects).
• Utilize PySpark in a Databricks environment to process large-scale datasets efficiently.
• Apply scientific programming techniques using SciPy, NumPy, and optimization methods.

Collaborate with business stakeholders to translate complex technical concepts into clear, actionable insights.

• Take full ownership of projects, work independently with minimal supervision, and manage sprints effectively.
• Work with GitHub Enterprise, CI/CD principles, and best practices for scalable data solutions.
• Focus on retail inventory management and operations research to drive significant business impact.