Natasha Tomar Email & Phone Number

Hyderabad, Telangana, India

1. Expertise in Recommendation Systems:• Proven track record of designing, implementing, and optimizing recommendation systems for various domains, leveraging collaborative filtering, content-based filtering, and hybrid approaches.• Strong understanding of machine learning algorithms and techniques, such as matrix factorization and deep learning, to enhance recommendation accuracy and personalization.• Experience in working with large-scale datasets, ensuring scalability and efficiency of recommendation algorithms.2. Proficiency in Reinforcement Learning:• Solid understanding and practical experience in reinforcement learning algorithms, including Q-learning, policy gradients, and deep reinforcement learning.• Demonstrated ability to develop and train reinforcement learning agents.• Familiarity with reward shaping, exploration-exploitation trade-offs, and model-based reinforcement learning techniques.3. Strong Background in Semantic Search and Skill-to-Role Matching:• In-depth knowledge of semantic search techniques, including natural language processing (NLP) and information retrieval, to enable accurate and context-aware search capabilities.• Experience in developing skill-to-role matching algorithms that leverage machine learning models to match candidate skills with job requirements.4. Large Language Models (LLMs)• Explored the capabilities and applications of large language models, including GPT-3, BERT, etc through extensive experimentation and analysis. Generated valuable insights on leveraging large language models to improve natural language processing task.

Hyderabad, Telangana, India

1. Role Normalization:• Demonstrated experience in utilizing advanced natural language processing techniques, such as BERT and FastText, to generate accurate and descriptive role name from fuzzy or incomplete role.• Proficient in applying state-of-the-art language models and embeddings to improve the consistency and quality of role normalization tasks.2. Data Augmentation:• Proven expertise in using data augmentation libraries and tools, such as Keras and PyTorch transforms, to enrich training datasets and enhance model performance.3. Data Curation:• Strong background in data cleaning, preprocessing, and transformation techniques to ensure high-quality and consistent data.• Experienced in handling missing values, outliers, and inconsistencies through strategies such as imputation, outlier detection, and data validation.4. Data Automation:• Hands-on experience in implementing data automation processes to streamline data workflows, improve efficiency, and minimize manual errors.5. Model Training and Deployment:• Extensive expertise in model training and development using frameworks like PySpark, enabling scalable and efficient training on large-scale datasets.• Demonstrated proficiency in deploying models using containerization technologies like Docker, facilitating easy and reproducible deployment across various environments.