Lead Data Scientist
10 hours ago
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.
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.
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