
Lead Data Scientist
2 days ago
We are looking for an experienced Lead Data Scientist to head our AI and Machine Learning initiatives. This role
is perfect for a professional who can drive innovation in Classical Machine Learning, Conversational AI, and Deep
Learning Systems while also providing technical leadership and strategic direction to a team of data scientists.
The Lead Data Scientist will be responsible for overseeing model development, optimizing AI-driven solutions,
mentoring junior team members, and collaborating with key stakeholders to align AI strategies with business
goals. The ideal candidate should possess deep expertise in NLP, Large Language Models (LLMs), Generative AI,
and MLOps to lead the development of scalable AI-driven solutions.
Responsibilities
- Define and drive the AI/ML strategy with alignment with business objectives.
- Lead the research, design, and development of cutting-edge machine learning and deep learning models,
including LLMs, GANs, VAEs, Transformers, CNNs, and RNNs.
- Establish best practices for data pipelines, feature engineering, model deployment, and AI governance.
- Evaluate emerging AI/ML technologies and recommend their adoption where beneficial.
- Architect and implement Generative AI solutions with a focus on improving conversational AI
experiences.
- Optimize LLMs (GPT, BERT, T5, etc.) for various business applications, including prompt engineering,
fine-tuning, and model interpretability.
- Work on text generation, semantic search, intent recognition, and AI-driven recommendation systems.
- Oversee end-to-end model lifecycle, from data collection and preprocessing to model deployment and
monitoring.
- Implement MLOps best practices to streamline model retraining, CI/CD for ML pipelines, and
productionization.
- Optimize models using hyperparameter tuning techniques such as grid search, Bayesian optimization,
and neural architecture search.
- Lead and mentor a team of data scientists and ML engineers
- Conduct code reviews, design discussions, and knowledge-sharing sessions.
- Guide junior team members on best practices in data science, deep learning, and software engineering.
- Partner with engineering, product management, and business stakeholders to integrate AI solutions into
production.
Qualifications & Experience
- Educational Background: Bachelor's or Master's in Computer Science, Data Science, AI, Statistics, or a
related field.
- Experience: 5+ years of hands-on experience in machine learning, deep learning, NLP, and AI-driven
applications.
- Machine Learning & AI: Proficiency in Classical ML (Regression, Decision Trees, Random Forests, SVMs,
Gradient Boosting, etc.) and Deep Learning (CNNs, LSTMs, GANs, Transformers, etc.).
Skills: data,deep learning,machine learning
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