Lead Data Scientist

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Position: Senior Lead Data Scientist

Location: USA - Chicago, Dallas, Atlanta, NY, Santa Clara

Experience Required: 12 - 18 Years

Total Experience Needed - 12-18 Years

A minimum of 5 years working with Python, Artificial Intelligence, Neural Networks, Natural Language Processing, Computer Vision, Machine Learning, and Data Science is essential.

Experience in Pre Sales activities is important.

Strong communication skills are a must.

We are seeking a knowledgeable Senior Lead Data Scientist / ML Engineer who brings a mix of pre-sales experience, team leadership, and technical skills in classical machine learning, deep learning, and generative AI. You will be responsible for engaging clients at a strategic level, propelling technical sales initiatives, and guiding a team to create and deploy pioneering ML solutions. This role is both strategic and hands-on, requiring innovative thinking and technical know-how.

Responsibilities

• Pre-Sales & Client Engagement
• Work alongside the sales and business development teams to understand client requirements and propose AI/ML solutions.
• Deliver presentations covering technical ideas, project outlines, and proof-of-concept (POC) demonstrations to clients and prospects.
• Break down intricate client needs into achievable project scopes, estimates, and technical proposals.
• Leadership & Team Management
• Guide, mentor, and provide constructive feedback to a group of data scientists and ML engineers.
• Set up best practices in solution design, code assessment, model validation, and deployment procedures.
• Lead the strategic plan for AI projects, ensuring consistency with organizational objectives and market dynamics.
• Classical Machine Learning & Statistical Modeling
• Utilize classical machine learning strategies such as regression, clustering, decision trees, and ensemble techniques to address a variety of business challenges.
• Design and enhance data workflows, feature engineering methods, and model selection approaches.
• Ensure rigorous model assessment, fine-tuning, and performance tracking in live environments.
• Deep Learning & Generative AI
• Create and manage deep learning models utilizing frameworks such as TensorFlow or PyTorch for tasks related to computer vision, NLP, or recommendation systems.
• Investigate and construct solutions that leverage generative AI technologies (GANs, VAEs, and transformer-based architectures) for cutting-edge product features.
• Encourage research and experimentation with the latest AI models to stay at the forefront of industry trends.
• Project Delivery & MLOps
• Oversee entire ML project lifecycles, from data analysis and model creation to implementation and ongoing support.
• Apply MLOps principles (CI/CD, containerization, model versioning) on cloud or on-premise systems.
• Work closely with DevOps and engineering teams to ensure seamless integration of ML solutions into existing infrastructures.
• Stakeholder Management & Communication
• Act as a central technical advisor for executive leadership, product managers, and client teams.
• Convey sophisticated AI/ML insights clearly and actionably to both technical and non-technical stakeholders.
• Promote a data-driven culture and encourage innovation within the organization.
  
  

Essential Qualifications

• Education & Experience
• Master’s or PhD in Computer Science, Data Science, Engineering, or a related discipline is preferred.
• A minimum of 12 years of relevant industry experience in data science or ML engineering, with 5 years in a leadership or managerial role.
• Technical Knowledge
• Pre-Sales: Proven experience in client-facing roles, solution development, and proposal writing.
• Classical ML: Proficient in traditional algorithms (regression, classification, clustering, etc.) and statistical techniques.
• Deep Learning: Practical knowledge in using frameworks like TensorFlow or PyTorch for CNNs, RNNs, transformer models, etc.
• Generative AI: Experience with GANs, VAEs, or large language models, with a evidence of building generative models.
• MLOps: Understanding of CI/CD processes, Docker/Kubernetes usage, and cloud services (AWS, Azure, GCP).
• Leadership & Communication
• Skills to mentor and lead data science/ML engineering teams effectively to achieve project objectives.
• Excellent communication abilities for engaging with clients, stakeholders, and executive teams.
• Familiarity with agile practices and project management, with the ability to juggle multiple projects at once.
  
  

Preferred Skills

• Experience with big data technologies (Spark, Hadoop) for extensive data processing tasks.
• Background in NLP, computer vision, or recommendation engine development.
• Knowledge of DevOps tools (Jenkins, GitLab CI, Terraform) for automating infrastructure.
• A record of published research or contributions to open-source AI initiatives.
  
  

Skills: artificial intelligence,docker,statistical modeling,artificial neural networks,generative ai,deep learning,project,spark,agile methodologies,ml,computer vision,big data,mlops,data science,aws,neural networks,machine learning,classical machine learning,pre sales,natural language processing,azure,kubernetes,project management,gcp,pytorch,python,tensorflow,hadoop,ci/cd