Data Science / ML Engineer

Key Responsibilities:

• Comprehend business issues:

  Propose valuable business solutions using statistical and AI/ML models.

• Model Design:

  Design statistical models and machine learning/deep learning models to address complex business challenges.

• Model Deployment:

  Develop and deploy ML/DL models into production environments.

• Data Insights:

  Formulate available data sources, augment them, and extract valuable insights using SQL and efficient query writing techniques.

• Data Visualization:

  Create innovative data visualizations and graphs using tools like d3js, dashplotly, and neo4j.

• Integration:

  Ensure seamless integration of AI/ML models into business processes using cloud platforms like AWS or Azure.

• Cross-Functional Collaboration:

  Work closely with cross-functional teams, translating business needs into actionable AI solutions.

• Agile Participation:

  Participate in agile project delivery, ensuring the timely execution of deliverables.

Required Technical Skills:

• Python Programming:

  Proficient in Python programming.

• Statistical Knowledge:

  Practical knowledge of Statistics and Operations Research methods.

• Frameworks and Tools:

  Hands-on experience with frameworks and tools such as Flask, PySpark, PyTorch, TensorFlow, Keras, Databricks, OpenCV, Pillow/PIL, Streamlit, and neo4j.

• Analytics/AI-ML Services:

  Expertise in Analytics/AI-ML AWS services, including SageMaker, Canvas, Bedrock.

• Predictive Modeling:

  Strong understanding of predictive modeling techniques like regression models, XGBoost, random forests, GBM, Neural Nets, SVM, etc.

• NLP Techniques:

  Proficient in NLP techniques like RNN, LSTM, and Attention-based models, with knowledge of Stanford NLP, IBM, Azure, and OpenAI NLP models.

• MLOps:

  Experience in MLOps: deploying models into production on AWS or Azure cloud platforms.

• Version Control:

  Working knowledge of version control tools such as GitHub and Bitbucket.

Soft Skills:

• Analytical Abilities:

  Strong analytical and problem-solving abilities.

• Communication Skills:

  Excellent communication, listening, and probing skills.

• Interpersonal Skills:

  Strong interpersonal skills, with the ability to collaborate and work effectively within a team.

Good to Have:

• AWS Specialty Certification in Data Analytics or Machine Learning.