Data Science Engineer job opening For People with Disability

R2.Data Science Engineer: Experience 2 to 9 Years

1. Mathematics and Statistics: A solid foundation in math and statistics is key for understanding data, modeling, and validation, including probability, hypothesis testing, and regression analysis.

2. Machine Learning Algorithms: Knowledge of supervised, unsupervised, and reinforcement learning algorithms is essential for tasks like classification, clustering, and recommendation systems.

3. Deep Learning & Neural Networks: Using neural networks (CNNs, RNNs, Transformer Models) to model complex data patterns, especially in image recognition and natural language processing.

4. Data Engineering: Skills in managing data pipelines (ETL), using tools like Hadoop and Spark for big data processing.

5. Data Visualization: Using tools like Matplotlib, Seaborn, and Tableau to create visuals that help communicate insights.

6. Data Wrangling and Preprocessing: Cleaning and transforming raw data, handling missing data, feature engineering, and normalization for effective model building.

7. Model Evaluation and Validation: Using cross-validation, performance metrics, and regularization techniques to ensure effective model performance.

8. Python & R Programming: Proficiency in Python and R for data manipulation, analysis, and machine learning with libraries like NumPy, Pandas, and Scikit-learn.

9. SQL and Database Management: Writing SQL queries, joining tables, and optimizing databases for efficient data extraction and manipulation.

10. Cloud Computing & Big Data Tools: Using cloud platforms (AWS, Azure, Google Cloud) and big data tools (Hadoop, Spark) for scalable data processing.

11. Version Control (Git): Using Git and platforms like GitHub/GitLab for collaborative data science projects and version control.

Location: Any location, but willing to relocate anywhere in India.ole & responsibilities

Preferred candidate profile

Perks and benefits