Senior Data Scientist

What you bring in:

• 5+ years of experience in designing, developing, and deploying ML models at scale, with a focus on NLP-driven solutions.
• Strong background in Natural Language Processing (NLP), including text classification, entity recognition, language modeling, and transformer-based architectures.
• Experience in building and deploying models at scale, handling millions of messages efficiently while maintaining performance and accuracy. Also working with on-device models.
• Ability to not only build ML models but also take ownership of deploying them into production, ensuring scalability, reliability, and monitoring.
• Knowledge of anomaly detection, adversarial ML techniques, and risk modeling to identify and prevent spam and fraudulent messaging activities.
• Strong ability to take ML models from research and experimentation to production, working closely with ML engineers and data engineers.
• Expertise in machine learning libraries such as TensorFlow, PyTorch, pandas and Scikit-learn, along with NLP-specific tools like Hugging Face Transformers, spaCy with experience in TFlife, ONNX.
• Hands-on experience fine-tuning LLMs including transformer-based architectures (BERT, GPT, LLaMA, T5, etc.) for domain-specific applications, including knowledge distillation, quantization, and model compression for efficiency.
• Strong ability to design, refine, and optimize prompts for LLM-based applications, ensuring high-quality responses and reduced model hallucinations.
• Ability to leverage data driven decision by experimentation, and statistical analysis to improve models and business outcomes.
• Strong understanding of designing, testing, and optimizing prompts for LLM-based applications to improve model accuracy and efficiency.
• Programming knowledge in at least one language, such as Python or R. Preferably python.
• Expert knowledge of machine learning algorithms.
• Familiarity with database modelling and data warehousing principles with a working knowledge of SQL
• Experience in building and optimizing large-scale data processing systems using Spark/PySpark
• Strong ability to work cross-functionally with engineers, product managers, and business stakeholders to align ML solutions with company objectives.