Lead Data Scientist - Artificial Intelligence

About the Role :

We are seeking a highly skilled and motivated Lead Data Scientist to spearhead our advanced analytics and AI initiatives. You will play a pivotal role in designing, developing, and deploying innovative machine learning and deep learning models that drive critical business decisions. The ideal candidate will have extensive experience in AI/ML frameworks, a deep understanding of data science methodologies, and the ability to lead and mentor a team of data scientists.

Key Responsibilities :

- Lead the end-to-end lifecycle of AI/ML projects including problem definition, data collection, preprocessing, model development, evaluation, deployment, and maintenance.

- Develop and implement state-of-the-art machine learning algorithms such as Artificial Neural Networks (ANN), XGBoost, deep learning models (CNNs, RNNs, Transformers), and ensemble techniques tailored to complex business challenges.

- Perform advanced feature engineering, data cleaning, and transformation to improve model robustness and predictive power.

- Optimize models by tuning hyperparameters, selecting the best algorithms, and employing techniques such as cross-validation and automated machine learning (AutoML).

- Collaborate closely with cross-functional teams including data engineering, product, and business stakeholders to integrate AI solutions seamlessly into production systems.

- Establish and enforce best practices in AI development: code versioning (Git), reproducibility, documentation, and model governance.

- Design scalable AI architectures to ensure robust model deployment and real-time inference capabilities in cloud or on-premise environments.

- Monitor model performance post-deployment, conduct root-cause analysis for model drift, and implement continuous learning pipelines.

- Stay abreast of emerging AI/ML research, tools, and frameworks, and champion adoption of innovative techniques within the team.

- Mentor and guide junior data scientists and analysts to enhance their technical capabilities and promote a culture of data-driven decision-making.

- Communicate complex analytical insights and AI concepts effectively to non-technical stakeholders and senior leadership.

Required Skills and Qualifications :

- Masters or PhD degree in Computer Science, Statistics, Mathematics, Engineering, or a related field.

- 7+ years of experience in applied machine learning, data science, or AI, with a track record of delivering impactful AI solutions in production.

- Strong expertise in machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn, XGBoost, LightGBM, or similar.

- Proficiency in programming languages such as Python or R, and experience with data manipulation libraries (Pandas, NumPy).

- Deep understanding of supervised, unsupervised, and reinforcement learning algorithms.

- Hands-on experience in deep learning architectures including CNNs, RNNs, Transformers, and GANs.

- Familiarity with cloud platforms such as AWS, Azure, or Google Cloud AI/ML services.

- Experience in building data pipelines, working with big data tools (Spark, Hadoop) is a plus.

- Knowledge of containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines for ML is preferred.

- Strong statistical analysis skills and knowledge of experimental design.

- Excellent problem-solving skills and the ability to think critically about data.

- Exceptional communication and leadership skills, with experience managing or mentoring technical teams.