Job Description

 Job Qualifications:

• Bachelors degree in Computer Science, Statistics, Mathematics, Data Science, or related field (Masters degree is a plus).
• Strong knowledge of supervised and unsupervised ML algorithms and statistical concepts.
• Proficiency in SQL and Python for data wrangling and preprocessing.
• Hands-on experience with forecasting models and time-series analysis (ARIMA, XGBoost, CatBoost, Prophet, LSTM).
• Familiarity with ETL pipelines, model deployment (Docker, APIs), and MLOps practices.
• Experience with cloud environments (AWS, GCP) and data visualization tools.
• Excellent analytical, problem-solving, and communication skills; ability to work collaboratively in a team environment.

Key Responsibilities:

• Develop and evaluate forecasting models using statistical and machine learning techniques.
• Contribute to model generation and optimization using ML algorithms.
• Perform data exploration and analysis (EDA) for feature engineering.
• Collaborate with operations teams to translate findings into actionable strategies.
• Design and maintain ETL pipelines for data processing.
• Deploy machine learning models into production environments and ensure ongoing maintenance using MLOps practices.
• Work with cloud platforms (AWS, GCP) for scalable model deployment.
• Ensure data integrity and quality throughout the pipeline.