Sr Data Scientist

FANATICS INC; Hyderabad City Taluka; On-site; PKR 2,500,000 - 3,500,000; Full time

Job summary

A leading supply chain solutions company in Pakistan is seeking an experienced data modeling professional to develop predictive models and optimize inventory. This role requires strong skills in Python, SQL, and collaboration with cross-functional teams. The ideal candidate has over 5 years of experience in building models for operational environments, particularly in time series forecasting and optimization techniques. This position offers opportunities for significant impact through tooling and automation.

Qualifications

• 5+ years of experience building and deploying models in a production or operational environment.
• Proficiency in Python (Pandas, Scikit-learn, NumPy) and SQL; experience with Spark or other distributed frameworks.
• Demonstrated experience with supervised/unsupervised learning and model evaluation techniques.
• Strong background in time series forecasting including classical and ML-based methods.
• Experience applying discrete optimization to real-world problems.
• Familiarity with simulation-based modeling and tradeoff analysis.
• Experience with data visualization tools and stakeholder-facing communication.

Responsibilities

• Develop and maintain predictive models across supply chain and inventory initiatives.
• Build and refine models for network optimization and inventory allocation.
• Perform exploratory analysis to understand performance drivers.
• Design and deploy time series models for demand forecasting.
• Collaborate closely with engineering, product, and operations teams.
• Build scalable pipelines and decision-support tools.

Skills

Modeling & Forecasting

Optimization & Simulation

Exploratory Analysis

Time Series Analysis

Cross-Functional Collaboration

Tooling & Automation

Strong communication skills

Education

Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Operations Research

Tools

Python

SQL

Spark

Data visualization tools

Job description

Key Responsibilities

• Modeling & Forecasting: Develop and maintain predictive models across supply chain and inventory initiatives — including forecasting models, classification, regression, clustering, and segmentation tasks.
• Optimization & Simulation: Build and refine models for network optimization, inventory allocation, sourcing, and internal transfers — using discrete optimization, simulation, and heuristic/metaheuristic techniques.
• Exploratory Analysis & Feature Development: Use EDA and statistical analysis to develop features, understand drivers of performance, and improve model design.
• Time Series Analysis: Design, test, and deploy time series models for demand forecasting, product performance tracking, and lifecycle modeling.
• Cross-Functional Collaboration: Work closely with engineering, product, and operations partners to frame problems, communicate insights, and translate models into decisions and tools.
• Tooling & Automation: Build scalable pipelines and decision-support tools using Python, Spark, and cloud-based infrastructure.

Qualifications

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Operations Research, or a related field
• 5+ years of experience building and deploying models in a production or operational environment
• Proficiency in Python (Pandas, Scikit-learn, NumPy) and SQL; experience with Spark or other distributed frameworks
• Demonstrated experience with supervised learning (regression, classification), unsupervised learning (clustering, dimensionality reduction), and model evaluation techniques
• Strong background in time series forecasting, including both classical (e.g., ARIMA, exponential smoothing) and ML-based methods (e.g., XGBoost, LSTM, DeepAR)
• Experience applying discrete optimization (e.g., MIP, constraint solvers, genetic algorithms) to real-world problems
• Familiarity with simulation-based modeling and tradeoff analysis
• Experience with data visualization tools (e.g., Superset, Tableau) and stakeholder-facing communication

Strong communication skills, with the ability to explain complex modeling approaches to technical and non-technical audiences