Data Scientist - Machine Learning Models (4-5 yrs)

Job Description :

- Design, develop, and deploy machine learning models using Python and other data science tools to derive actionable insights.

- Work with MongoDB for managing and analyzing large datasets, ensuring effective storage and retrieval of data.

- Collaborate with engineering and product teams to integrate machine learning models into production systems and provide data-driven solutions.

- Leverage Azure cloud services (e.g., Azure Machine Learning, Azure Databricks) to scale and optimize machine learning workflows and data pipelines.

- Implement data preprocessing and feature engineering techniques to enhance model performance.

- Analyze and visualize large and complex datasets to generate insights and make recommendations for business strategy.

- Optimize and fine-tune existing machine learning models for better performance and accuracy.

- Build and maintain robust data pipelines, working with structured and unstructured data.

- Ensure the quality, consistency, and accuracy of data used for model building and analysis.

- Stay updated with the latest trends in data science, machine learning, and AI technologies.

- Communicate results and insights effectively to non-technical stakeholders through data visualizations and reports.

- Data Scientist, with a strong track record of deploying machine learning models into production.

- Strong programming skills in Python, with experience in libraries like Pandas, NumPy, SciPy, Scikit-learn, TensorFlow, or PyTorch.

- Hands-on experience with MongoDB for managing large datasets and performing analytics.

- Proficiency in working with Azure cloud services, especially Azure Machine Learning, Azure Databricks, and Azure SQL.

- Strong understanding of statistical methods, data modeling, and machine learning algorithms (e.g., classification, regression, clustering, deep learning).

- Experience with data wrangling, feature engineering, and building robust data pipelines.

- Familiarity with data visualization tools like Power BI, Tableau, or Matplotlib.

- Excellent problem-solving skills, attention to detail, and the ability to work in a fast-paced environment.

- Strong communication skills, with the ability to present complex data science concepts to non-technical stakeholders.

- Experience in deploying machine learning models using cloud-based platforms such as Azure Machine Learning Service or Azure Kubernetes Service.

- Familiarity with Big Data technologies such as Hadoop or Spark.

- Knowledge of advanced AI topics like natural language processing (NLP) or computer vision.

- Experience with containerization technologies like Docker and orchestrating ML workflows with Kubernetes.

- Strong knowledge of SQL and data querying languages.

- Experience with Agile methodologies and working in collaborative team environments.