Data Scientist

• Collect, clean, and preprocess structured and unstructured data.
• Analyze large datasets to identify trends, patterns, and business opportunities.
• Develop and deploy machine learning and predictive analytics models.
• Perform statistical analysis and hypothesis testing.
• Build recommendation systems, forecasting models, and classification/regression models.
• Develop dashboards and visualizations to communicate insights.
• Work with engineering teams to deploy models into production.
• Optimize model performance through feature engineering and hyperparameter tuning.
• Collaborate with stakeholders to understand business requirements and translate them into data solutions.
• Document methodologies, experiments, and model performance.
• Stay updated with advancements in AI, machine learning, and data science technologies.

Required Skills

• Python
• R (Preferred)
• SQL
• Machine Learning
• Deep Learning
• Statistics & Probability
• Data Analysis
• Data Visualization
• Predictive Modeling
• Feature Engineering
• Natural Language Processing (NLP)
• Computer Vision (Preferred)
• Generative AI & LLMs (Preferred)
• TensorFlow
• PyTorch
• Scikit-learn
• Pandas
• NumPy
• Matplotlib / Power BI / Tableau
• Git
• Cloud Platforms (AWS, Azure, GCP)
• Problem Solving
• Communication Skills

Preferred Experience

• Experience with Python-based machine learning frameworks.
• Knowledge of big data technologies such as Spark, Hadoop, or Databricks.
• Experience deploying ML models using Docker, Kubernetes, or MLOps tools.
• Familiarity with cloud-based AI/ML services.
• Experience with LLMs, prompt engineering, RAG, vector databases, or AI agents is an advantage.