Key Responsibilities:
- Develop and implement advanced machine learning models, particularly focused on time series forecasting.
- Perform data preprocessing, feature engineering, and exploratory data analysis to extract meaningful insights from large datasets.
- Evaluate model performance using appropriate metrics and refine models for improved accuracy and efficiency.
- Should have extensive experience in developing time series models which was deployed or used at the client side.
- Develop and maintain documentation for models, processes, and code to ensure reproducibility and knowledge sharing.
- Communicate results and insights effectively to both technical and non-technical stakeholders.
Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Data Science, Economics or a related field;
- Strong programming skills in Python and SQL
- In-depth knowledge of machine learning algorithms, statistical methods, and time series analysis techniques.
- Hands-on experience with time series forecasting models such as ARIMA, SARIMA, Exponential Smoothing, Prophet, LSTM, and others.
- Proficiency with data manipulation and visualization tools such as Pandas, NumPy, Matplotlib, and Seaborn.
- Ability to work independently, manage multiple projects, and meet tight deadlines in a fast-paced environment.
- Strong analytical and problem-solving skills with attention to detail.
- Excellent communication skills, with the ability to explain complex analytical concepts to non-technical audiences.
Preferred Qualifications:
- Experience with cloud platforms such as AWS, GCP, or Azure for deploying machine learning models.
- Some experience in GenAI is preferred.