Data Scientist

4 days ago


Gurugram Haryana, India Apps Associates Full time

Role: 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.
- 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


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