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We are looking for a Data Scientist who is passionate about applying machine learning to solve real-world business problems such as sales forecasting, demand prediction, and optimization modeling. This role will work closely with cross-functional teams to design, develop, and deploy advanced analytics models that drive tangible business outcomes.
Job Responsibility:
Develop predictive models for business use cases such as Sales Forecasting, Demand Planning, Inventory Optimization, etc.
Design optimization algorithms to improve resource allocation, pricing strategies, and operational efficiency
Perform data preprocessing and feature engineering on structured and unstructured datasets
Deploy and monitor machine learning models in production environments (using Azure Machine Learning or similar platforms)
Collaborate with business stakeholders to understand requirements, define success criteria, and translate them into analytical solutions
Communicate insights and model results to both technical and non-technical audiences through reports, dashboards, or presentations
Continuously research and experiment with new techniques to enhance model performance and reliability
Requirements:
Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or related fields
2+ years of practical experience building machine learning models for business applications (especially time-series forecasting and optimization problems)
Solid understanding of Supervised Learning, Time Series Modeling (ARIMA, Prophet, LSTM, etc.), Optimization Techniques (Linear Programming, Heuristic Methods, etc.)
Hands-on experience with Python, SQL, and machine learning frameworks (e.g., Scikit-Learn, TensorFlow, PyTorch)
Experience working with Azure Machine Learning, Databricks, or other cloud-based ML platforms is a strong plus
Familiarity with MLOps practices and deployment techniques is a bonus
Strong analytical thinking, problem-solving skills, and business acumen
Nice to have:
Experience with sales forecasting models or inventory/demand optimization projects
Experience integrating models with Power BI, Microsoft Fabric, or similar BI tools
Knowledge of model explainability techniques (e.g., SHAP, LIME) to build trust with business users
Understanding of data engineering concepts (ETL/ELT pipelines) is a plus
What we offer:
Work on real-world, high-impact Data & AI projects
Opportunity to innovate and lead AI-driven initiatives for top enterprise clients
Competitive salary and performance-based bonus
Professional training and certifications supported (Microsoft Azure AI, Machine Learning, etc.)
A collaborative, agile, and innovation-driven work culture