Description

You will apply advanced analytical techniques and machine learning to drive data-driven decision making.

Responsibilities

• Translate business needs into specific analytics and reporting requirements.
• Manage the full machine learning lifecycle, including feature engineering, training, validation, scaling, deployment, and monitoring.
• Leverage ML and LLM technologies to extract actionable insights from datasets.
• Apply supervised and unsupervised learning techniques for classification, forecasting, and anomaly detection.
• Implement pattern recognition using decision trees, regressions, ensemble methods, and boosting algorithms.

Required Skills

• 5–7 years of experience in data science or a similar role.
• Master’s degree or PhD in Computer Science, Statistics, Applied Mathematics, or a related field.
• Proficiency in Python (preferred) or R.
• Experience with machine learning libraries such as TensorFlow, PyTorch, or scikit-learn.
• Strong knowledge of Natural Language Processing (NLP).
• Expertise in descriptive statistics, optimization, cluster analysis, and pattern recognition.
• Hands-on experience with SQL, Tableau, or Power BI.
• Experience with cloud computing environments (GCP) and data platforms like Databricks or Spark.

Preferred Skills

• Experience with AWS.

Key Skills

Education

Bachelor's degree in Computer Science