Ability to combine quantitative data with business domain knowledge with large datasets and derive summaries/insights.
Clean, prepare, and analyze complex datasets for ML algorithms, knowledge of statistical methodology and analysis with advanced programming skills to perform exploratory data analysis with large datasets.
Design, build, deploy, and refine large-scale machine learning models and algorithmic decision-making systems that solve real-world problems for customers
Experience in Machine learning algorithms, model implementation, and optimization to solve Regression, Classification, and Segmentation problems.
Experience in forecasting algorithms, model implementation, and optimization
Experience with ML frameworks/libraries and NLP e.g. Scikit-learn, Pandas, Matplotlib, Seaborn, Tensor flow or PyTorch, etc.
Experience in deploying ML algorithms in cloud platforms such as Azure, and AWS.
Contribute to data quality control, model validation, and model explainability investigation.
Ability to work in a fast-paced environment, using new techniques and algorithms best suited for solving challenging problems.
Requirements & Skills:
Strong proficiency in Python, Ro Experience with SQL – Snowflake, SSIS
In-depth knowledge of statistical, ML, and forecasting algorithms Experienced with deployments of ML models in any of the cloud architectures – Azure, AWS, or GCP
Familiarity with version control and CI/CD – Git
Strong problem-solving skills and the ability to think critically and creatively to develop innovative solutions.
Excellent communication and interpersonal skills.
Strong problem-solving abilities and attention to detail.
Ability to work collaboratively in a team environment and manage multiple tasks effectively.
Maintain thorough documentation of reports, data models, and processes.
Utilize task management tools (e.g., Monday, JIRA, Trello) to track progress and manage workload.
