Lead Data Scientist

About Our Client

The organization operates as an elite, high-growth data and artificial intelligence consultancy, specialized in empowering modern enterprises to develop sophisticated strategies, robust technology architecture, and high-performing technical teams required to unlock exponential growth and operational efficiency. The company directly addresses the complex structural challenges of data fragmentation and AI scaling by seamlessly embedding world-class engineering professionals directly into client teams and capitalizing on powerful strategic alliances with elite technology providers—including Snowflake, AWS, Google Cloud, and Databricks. Following a high-profile recent acquisition of a specialized machine learning and AI consultancy, the organization has uniquely consolidated its diverse capabilities, blending cutting-edge research with practical enterprise deployment to serve a global portfolio of clients with a uniquely versatile talent mix.

About the Opportunity

The Lead Data Scientist will step into a highly visible, strategic technical role responsible for driving the conceptualization, development, and scaling of advanced machine learning solutions across a diverse array of client engagements, ranging from agile tech startups to Fortune 500 corporations. This position dynamically fuses hands-on algorithmic contribution with elite technical leadership, charging the lead with mentoring specialized engineering staff and managing high-value client relationships from initial project scoping through final production delivery. Serving as a primary engine of innovation, this role is critical to translating abstract business obstacles into concrete, high-impact ML solutions tailored perfectly to unique industry environments.

Responsibilities

• Lead end-to-end client consulting engagements, taking complete structural ownership of scoping requirements, solution architecture, executive expectation management, and final production delivery
• Direct agile, small-scale project squads, serving as the primary strategic and technical point of contact for client leadership teams
• Architect, train, optimize, and deploy advanced machine learning systems across highly diverse business domains, datasets, and enterprise use cases
• Navigate and orchestrate complex deployment pipelines across varied infrastructure environments—including managed cloud ML platforms and custom containerized Python applications on elastic cloud infrastructure
• Mentor, guide, and elevate the technical capabilities of junior and senior data scientists, directly influencing best practices and engineering standards across the wider data science unit
• Continuously evaluate, stress-test, and integrate emerging open-source tools, algorithmic frameworks, and methodologies to solve complex client bottlenecks

Requirements

• Six (6+) or more years of progressive, practical machine learning experience with a verifiable, proven track record of successfully deploying predictive models into live production environments
• Prior professional experience operating within a consulting firm, agency, or external client-facing capacity, demonstrating advanced skills in managing project scopes, communicating technical risks, and maintaining high client confidence
• Deep subject-matter expertise in at least one specialized domain: predictive/classical ML, computer vision (CV), or large language models (LLMs) and advanced multi-agent systems, paired with a natural adaptability to learn and cross-train in adjacent fields
• Mastery across modern deployment stacks, including managed cloud ecosystem tools (AWS SageMaker, Azure ML) and highly customized containerized environments utilizing Python, Docker, and core infrastructure like AWS EC2
• Absolute fluency in Python and SQL, supported by deep familiarity with Git version control and core ML frameworks (e.g., PyTorch, Scikit-learn, Hugging Face transformers) calibrated to your technical specialization
• Proven production experience with robust experiment tracking, artifact logging, and complete MLOps lifecycle management tools (such as MLflow or Weights & Biases)
• Possession of an advanced degree (M.S. or Ph.D.) in a highly quantitative discipline (e.g., Computer Science, Data Science, Statistics, Mathematics, or Physics) or equivalent demonstrated practical engineering expertise
• Exceptional communication and narrative skills, with a proven ability to explain complex algorithmic behaviors, model metrics, and trade-offs clearly to both highly technical engineers and non-technical corporate executives
• Geographic Constraint: Must be currently based and legally authorized to work within the United States or Canada

Pay Range and Compensation Package

The target baseline salary framework is $160,000 to $200,000 USD annually. Final base salary placement within this competitive tier is calibrated dynamically based upon the candidate's core data science tenure, geographic location, consulting background, and specialized model architecture proficiencies. The total rewards portfolio features a highly competitive annual base salary structure, explicitly noting that this targeted baseline range excludes additional performance-driven corporate bonuses, potential equity options, or expanded enterprise benefits.

Benefits & Perks

• Premium corporate medical, vision, and dental insurance plans fully paid by the company for complete peace of mind
• Comprehensive home office infrastructure support, including top-tier company-provided technology, laptop, and workspace equipment setup
• Outstanding work-life flexibility featuring generous, self-managed vacation structures and paid sick leave frameworks
• A highly supportive, collaborative, and team-oriented remote culture built on continuous knowledge sharing and technical excellence
• Exciting company-sponsored team gatherings, localized corporate events, and premium, custom brand merchandise

Equal Opportunity Statement

The client is an equal opportunity employer. They celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, or national origin. Note: RemoteHunter is not the Employer of Record (EOR) for this role. Our purpose in this opportunity is to connect exceptional candidates with leading employers. We help job seekers worldwide discover roles that match their goals and guide them to complete their full application directly through the hiring company’s career page or ATS.