Data Science Specialist

Aygaz; Fatih; On-site; TRY 80,000 - 140,000; Full time

Job summary

Aygaz is seeking a Data Analytics professional to own analytical workstreams across optimization, forecasting, pricing analytics, and image-based analytics. You will collaborate with data scientists, data architects, and business stakeholders to deliver production-ready solutions for smarter distribution and decision-making.

Responsibilities include end-to-end LPG supply planning, demand forecasting, and GIS-based planning, with opportunities to implement LLM-driven insights and automated

Qualifications

• BSc or MSc in Engineering, CS, Data Science, Mathematics, Statistics, Industrial Engineering, or related quantitative field
• 1–3 years hands-on data science/analytics/machine learning/optimization experience
• Strong Python and SQL for data prep, analysis, modeling
• Knowledge of forecasting, regression, classification, tree-based models or deep learning
• Interest in PyTorch, NVIDIA stack, Gurobi, GeoPandas GIS, and LLM frameworks
• Good communication and collaboration with stakeholders
• Good command of English

Responsibilities

• Own assigned analytical workstreams from framing to production-ready solutions
• Route and fleet optimization for distribution planning and logistics efficiency
• End-to-end LPG supply and inventory planning including sourcing and vessel ops
• Demand forecasting, pricing analytics, customer analytics, decision-support models
• Deep learning models and image-based analytics for automation
• GIS-based analytics, polygon processing, map-enabled planning
• LLM-driven insights and intelligent assistants
• Turn outputs into clear recommendations for stakeholders
• Collaborate with data architecture, BI, and technology teams to deploy and monitor solutions

Skills

Python

SQL

Forecasting

Machine learning

Education

BSc or MSc in Engineering, CS, Data Science, Math, Statistics

Tools

PyTorch

NVIDIA stack

Gurobi

GeoPandas

LLM frameworks

Job description

Aygaz Data Analytics Team plays a central role in the company’s data-driven transformation agenda, delivering strategic, executive-sponsored initiatives that improve operational efficiency, strengthen sales and profitability, and enable scalable decision-making across core and emerging business areas. Our portfolio brings together optimization, forecasting and pricing analytics, geospatial planning, deep learning, selected image-based analytics, and LLM-enabled automation to solve complex business problems with measurable impact. We work closely with business units to understand Aygaz’s end-to-end domain, translate problems into analytical solutions, and build standardized, insight-led processes that can be adopted across the organization. In this role, you will own assigned analytical workstreams within this portfolio while learning from experienced data scientists, data architects and business stakeholders.

Qualifications

• BSc or MSc degree in Engineering, Computer Science, Data Science, Mathematics, Statistics, Industrial Engineering, or a related quantitative field
• 1-3 years of hands-on experience in data science, analytics, machine learning, or optimization projects
• Strong practical skills in Python and SQL for data preparation, analysis, modeling and experimentation
• Working knowledge of modeling concepts such as forecasting, regression, classification, tree-based models, or deep learning
• Curiosity to explore tools such as PyTorch, NVIDIA stack, Gurobi, GeoPandas/GIS, and LLM frameworks with expert guidance
• Ability to understand business problems, question assumptions, communicate insights clearly, and work collaboratively with technical and non-technical stakeholders
• Good command of English

Job Description

• Own assigned analytical workstreams from problem framing and data exploration to production-ready solutions in selected areas of our portfolio.
• Route and fleet optimization for smarter distribution planning, field operations, and logistics efficiency.
• End-to-end LPG supply and inventory planning, from sourcing and vessel operations to inter-facility transfers and sales dispatches.
• Demand forecasting, pricing analytics, customer analytics, and decision-support models using structured and unstructured data.
• Deep learning models and selected image-based analytics use cases that support automation and performance improvement.
• GIS-based analytics, polygon processing, and map-enabled planning for network and territory design.
• LLM-driven insights, intelligent assistants, chatbot capabilities, and agentic business workflows.
• Turn analytical outputs into clear recommendations for business stakeholders.
• Collaborate with data architecture, BI, and technology teams to deploy, monitor, and continuously improve solutions.