Data Scientist

Data Scientist

Skills:

• 5+ years of experience in data science and machine learning, focusing on recommendation systems and NLP.
• Strong proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch) for ML development.
• Experience with NLP techniques such as embeddings, transformers, topic modeling, and named entity recognition.
• Hands-on experience with ML model deployment and MLOps practices using AWS SageMaker, Lambda, and Step Functions.
• Proficiency in working with large-scale datasets, SQL/NoSQL databases, and data processing frameworks.
• Strong knowledge of feature engineering, model evaluation, and hyperparameter tuning.
• Familiarity with vector search technologies (e.g., Amazon OpenSearch).
• Experience with API development for serving ML models using Flask, FastAPI, or AWS API Gateway.
• Ability to work in an Agile environment and collaborate with cross-functional teams.
• Excellent problem-solving and analytical skills with the ability to translate business requirements into ML solutions

Key Responsibilities:

• Design, develop, and optimize ML models for expert and expertise recommendation using state-of-the-art techniques.
• Implement Natural Language Processing (NLP) algorithms for entity recognition, topic modeling, and semantic search.
• Develop and maintain ML pipelines for model training, evaluation, deployment, and monitoring in AWS.
• Work with structured and unstructured data, performing feature engineering and data preprocessing to improve model accuracy.
• Deploy and manage ML models using AWS SageMaker, Lambda, Step Functions, and API Gateway.
• Collaborate with data engineers and software developers to integrate ML models into production applications.
• Implement A/B testing and model performance evaluation metrics to ensure optimal model effectiveness.
• Optimize ML models for scalability, performance, and cost-efficiency in a cloud environment.
• Ensure ML solutions adhere to security, privacy, and compliance best practices.
• Stay up to date with emerging trends in ML, AI, and data science, continuously improving models and methodologies