Lead Data Scientist

ZipRecruiter; Santa Clara (CA); On-site; USD 150,000 - 200,000; Full time

Job summary

A leading company is seeking a Senior Lead Data Scientist to drive technical sales strategies and lead innovative AI/ML solutions. This strategic role requires strong leadership skills, technical expertise in machine learning and generative AI, coupled with the ability to engage clients effectively. Ideal candidates will have a Master's or PhD and extensive experience proving their expertise in the field. You'll collaborate with various teams to ensure the delivery of cutting-edge projects and foster a culture of innovation.

Qualifications

• 12 years of industry experience in data science or ML engineering.
• 5 years in a leadership role.
• Expertise in classical ML, deep learning, generative AI, and MLOps.

Responsibilities

• Engage in pre-sales client discussions; collaborate with sales teams.
• Lead ML project lifecycles from data exploration to deployment.
• Provide mentorship and direction to data scientists and ML engineers.

Skills

Python

Artificial Intelligence

Neural Networks

Natural Language Processing

Computer Vision

Machine Learning

Data Science

Pre-sales

Team Leadership

Technical Proficiency

Education

Master’s or PhD in Computer Science, Data Science, Engineering

Tools

TensorFlow

PyTorch

Spark

Hadoop

Jenkins

GitLab CI

Terraform

Job description

Job Description

Senior Lead Data Scientist

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

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 and strong communication skills are mandatory.

We are looking for an experienced Senior Lead Data Scientist / ML Engineer with a strong blend of pre-sales, 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

1. Pre-Sales Client Engagement

• Collaborate with 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.

1. Leadership & Team Management

• Provide direction, mentorship, and performance feedback to data scientists and ML engineers.
• Establish best practices in solution design, code reviews, model validation, and deployment.
• Drive the strategic roadmap for AI initiatives in alignment with organizational goals and market trends.

1. Classical Machine Learning & Statistical Modeling

• Apply techniques such as regression, clustering, decision trees, and ensemble methods to solve business problems.
• Design and optimize data pipelines, feature engineering, and model selection strategies.
• Ensure robust model evaluation, tuning, and performance monitoring in production.

1. Deep Learning & Generative AI

• Develop and maintain deep learning models using frameworks like TensorFlow or PyTorch for tasks like computer vision, NLP, or recommendation systems.
• Explore and build solutions leveraging generative AI (GANs, VAEs, transformers) for innovative features.
• Stay ahead of industry advances through research and experimentation.

1. Project Delivery & MLOps

• Lead end-to-end ML project lifecycles from data exploration to deployment and maintenance.
• Implement MLOps best practices such as CI/CD, containerization, and model versioning on cloud or on-premise infrastructures.
• Collaborate with DevOps teams to integrate ML solutions seamlessly.

1. Stakeholder Management & Communication

• Serve as a technical advisor to leadership, product managers, and clients.
• Communicate complex AI/ML findings clearly to technical and non-technical audiences.
• Promote data-driven decision-making and a culture of innovation.

Required Qualifications

• Master’s or PhD in Computer Science, Data Science, Engineering, or related field.
• 12+ years of industry experience in data science or ML engineering, with 5+ years in leadership roles.
• Technical expertise in pre-sales, classical ML, deep learning, generative AI, and MLOps.
• Strong leadership and communication skills, with experience mentoring teams and engaging with clients.

Bonus Skills

• Experience with big data ecosystems (Spark, Hadoop).
• Background in NLP, computer vision, or recommendation systems.
• Knowledge of DevOps tools (Jenkins, GitLab CI, Terraform).
• Research publications or contributions to open-source AI projects.