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.

Skills Required
Data Science, Tensorflow, Pyspark, Keras, Pytorch, Statistical Knowledge, Databricks, Python, Artificial Intelligence and Machine Learning