Lead Data Scientist
4 weeks ago
Key Responsibilities :
- Work on new initiatives for Machine Learning using conversational NLP techniques and introduce ML-based learning for recommendation and coaching assistant in our products
- Work with the engineering teams and ensure timely deliveries.
- Be part of a global Engineering team supporting Fortune 1000 customers worldwide.
- Ability to experiment and iterate rapidly and provide tangible improvements in the overall engagement
You've Got What It Takes If You Have :
- Master's or bachelor's degree in computer science or a related study or equivalent experience.
- 6+ years of hands-on experience architecting and designing highly scalable and resilient systems.
- Experience in designing & scaling applications based on Data Science, NLP, and conversational AI
- Understanding of ML algorithms - classical and deep learning and ML frameworks
- Good understanding of system availability, security, and performance management.
- Hand-s on work experience in: PyTorch and its ecosystem of libraries, Word and document embeddings, Transformers and Attention, RNN, LSTM, A background in BERT and its variants, transfer-learning practices,
- NLP Libraries: NLTK, Genism , Spacy, ML-pipelines - Apache Airflow/ Kubeflow/ RAY, OpenAI libraries and Models - LLMs, scikit-learn, Pandas, Numpy , plotting using matplotlib, seaborn, HuggingFace.
Beside the knowledge of framework or libraries, having experience in building the recommendation systems with following algorithms will be considered as a plus :
- Generative Models i.e. VAE & GAN
- Collaborative based filtering/ Context aware/Graph based recommender systems
- Factorization Machine, Deep recommender
Experience with any of the following is considered a plus :
- TensorFlow, Big-data and PySpark
- Data wrangling libraries: Beautiful Soup or Scrapy
- R libraries, Taking models to production
- Cloud Technologies: GCP/AWS
- ML Graph Models GNN and NetworkX
MUST HAVE SKILL : Mandatory NLP and Gen-AI hands-on experience
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