Description
Job Summary:
We are seeking a part-time Data Scientist to support key initiatives in optimization and advanced analytics, working on concrete, high-value business problems.
Key Highlights:
1. Maximize impact in fewer hours, focused on high business value
2. Participate in the design and improvement of logistical and commercial impact models
3. Continuous learning environment and meritocracy
Data Scientist – Operations and Logistics (Part-Time)
Location: Peru (Remote)
Work Mode: 100% Remote
Schedule: Part-time – 4 hours per day
Department: Operations / Data
Reports To: Operations Manager / Head of Data
Seniority Level: Semi-Senior / Senior
About the Role
We are looking for a part-time Data Scientist residing in Peru to support key initiatives in optimization and advanced analytics. This role is designed for professionals who wish to maximize impact in fewer hours, working on concrete, high-value business problems.
You will participate in designing and improving models that directly impact logistical and commercial operations, with a focus on optimization, forecasting, and data-driven decision-making.
Key Responsibilities
Develop and improve demand forecasting models.
Implement logistical optimization solutions (routing, picking, loading).
Analyze operational and commercial data to generate actionable insights.
Collaborate on deployment and maintenance of models in GCP (as per project scope).
Responsibility scope will be aligned with the 4-hour daily schedule, prioritizing impact and efficiency.
Technical Requirements
Mandatory
Advanced Python (Pandas, NumPy).
Experience in applied Machine Learning and/or mathematical optimization.
Advanced SQL.
Prior experience working with business or operational data.
Desirable
Knowledge of Google OR-Tools.
Experience in cloud environments (ideally GCP).
Technical English.
Candidate Profile
Strong synthesis ability and focus.
Results-oriented mindset and prioritization skills.
Autonomy and effective time management.
What We Offer?
Remote work within Peru.
Flexible schedule aligned with part-time arrangement.
Real-world projects with high operational impact.
Continuous learning environment and meritocracy.
Employment Type: Part-Time
Expected Hours: 20 per week
Work Location: Remote