Posted on: 20/09/2025
About the Role :
In this role, you will leverage your expertise to develop, implement, and optimize advanced models that deliver actionable insights and drive strategic business decisions.
Youll work closely with cross-functional teams to translate complex data into meaningful solutions that impact our products and services.
Key Responsibilities :
- Analyze large and diverse datasets to identify patterns, trends, and opportunities for optimization.
- Collaborate with product managers, engineers, and domain experts to understand requirements and translate them into robust data-driven solutions.
- Perform data preprocessing, feature engineering, and model evaluation to ensure accuracy and reliability.
- Continuously monitor, validate, and improve existing models in production.
- Communicate findings, insights, and technical concepts clearly to non-technical stakeholders through visualizations, reports, and presentations.
- Stay current with the latest advancements in machine learning, AI, and data science to recommend innovative approaches.
- Contribute to building scalable data pipelines and integrating ML models into production environments.
- Participate in research and development activities to explore novel modeling techniques and tools.
Requirements :
- 5+ years of professional experience in data science, machine learning, or predictive analytics.
- Strong programming skills in Python or R, with experience in ML libraries such as scikit-learn, TensorFlow, PyTorch, or similar.
- Expertise in statistical modeling, regression, classification, clustering, and time series forecasting.
- Experience with data preprocessing, feature selection, dimensionality reduction, and model validation techniques.
- Proficiency in SQL and working with large-scale datasets using platforms like Hadoop, Spark, or cloud-based data warehouses.
- Familiarity with deploying machine learning models using APIs or cloud services (AWS, GCP, Azure).
- Excellent problem-solving skills and ability to work independently and collaboratively in a team
environment
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