What are the responsibilities and job description for the Lead Data Scientist position at YO HR CONSULTANCY?
Job Description
Job Description
Senior Lead Data Scientist
Location : USA - Chicago, Dallas, Atlanta, NY, Santa Clara
Experience : 12 - 18 Years
Total Experience - 12-18 Years&
Minimum 5 years of experience in Python, Artificial Intelligence, Neural Networks, Natural Language Processing, Computer Vision, machine learning, and data science.&
Pre Sales experience
ability to communicate really well is mandatory.
We are looking for an experienced& Senior Lead Data Scientist / ML Engineer & with a strong blend of& pre-sales & expertise,& team leadership , and& technical proficiency & across classical machine learning, deep learning, and& generative AI . You will engage in high-level client discussions, drive technical sales strategies, and lead a team to design and implement cutting-edge ML solutions. This is a strategic role requiring both thought leadership and hands-on technical contributions.
Roles Responsibilities
Key Responsibilities
- Pre-Sales Client Engagement
- Collaborate with the sales and business development teams to identify client needs and formulate AI / ML solutions.
- Present technical concepts, project proposals, and proof-of-concepts (POCs) to prospects and clients.
- Translate complex client requirements into actionable project scopes, estimates, and technical proposals.
- Leadership Team Management
- Provide direction, mentorship, and performance feedback to a team of data scientists and ML engineers.
- Establish best practices in solution design, code reviews, model validation, and production deployment.
- Drive the strategic roadmap for AI initiatives, ensuring alignment with organizational goals and market trends.
- Classical Machine Learning Statistical Modeling
- Apply classical machine learning techniques (e.g., regression, clustering, decision trees, ensemble methods) to solve diverse business problems.
- Design and optimize data pipelines, feature engineering processes, and model selection strategies.
- Ensure robust model evaluation, tuning, and performance monitoring in production environments.
- Deep Learning Generative AI
- Develop and maintain deep learning models using frameworks such as TensorFlow or PyTorch for tasks like computer vision, NLP, or recommendation systems.
- Explore and build solutions leveraging generative AI (GANs, VAEs, or transformer-based architectures) for innovative product features and services.
- Champion research and experimentation with state-of-the-art AI models, staying ahead of industry advances.
- Project Delivery MLOps
- Lead end-to-end ML project lifecycles, from data exploration and model development to deployment and post-launch maintenance.
- Implement MLOps best practices (CI / CD, containerization, model versioning) on cloud or on-premise infrastructures.
- Collaborate with DevOps and engineering teams to integrate ML solutions seamlessly into existing systems.
- Stakeholder Management Communication
- Serve as a key technical advisor to executive leadership, product managers, and client teams.
- Communicate complex AI / ML findings in clear, actionable terms to both technical and non-technical audiences.
- Advocate data-driven decision-making and foster a culture of innovation within the organization.
Required Qualifications
Preferred / Bonus Skills
