Director Data Science

Straive; United States; Remote; USD 230,000 - 350,000; Full time

Job summary

Straive is seeking an experienced Director of Data Science to lead a high-performing team of data scientists and ML engineers. This executive role bridges technical innovation with business strategy and includes serving as a key client-facing partner.

You will own strategic account relationships, translate complex business challenges into cutting‑edge AI/ML solutions, guide production ML practices (MLOps), and help scale data products across major accounts while driving measurable business

Qualifications

• 14+ years of experience in data science and AI.
• Experience leading data science teams and client-facing partnerships.
• Strong understanding of ML/AI with production ML engineering practices.

Responsibilities

• Act as primary technical interface for executive client stakeholders and demonstrate ROI.
• Drive long-term vision for data science and AI adoption across key accounts.
• Partner with business development to identify data opportunities, define proposals, and participate in client pitches.
• Manage, recruit, and mentor a multi-disciplinary team of Senior Data Scientists, Machine Learning Engineers, and AI Researchers.
• Oversee end-to-end data product lifecycle from discovery to production deployment (MLOps) and monitoring.

Job description

We are seeking an experienced Director of Data Science with 14+ years of expertise in the data science and AI ecosystem to lead, scale, and mentor our high‑performing team of data scientists and machine learning engineers. In this executive leadership role, you will bridge the gap between technical innovation and business strategy. You will serve as a key client‑facing partner, owning strategic account relationships, translating complex business challenges into cutting‑edge AI/ML solutions, and providing hands‑on technical guidance to your engineering teams.

Key Responsibilities

Strategic & Client Leadership

• Client & Stakeholder Management: Act as the primary technical interface for executive client stakeholders. Understand their core business imperatives, present complex AI/ML strategies, and demonstrate measurable ROI from data science initiatives.
• Solution Architecture & Strategy: Drive the long‑term vision for data science and AI adoption across key accounts, translating business problems into high‑impact statistical, machine learning, and generative AI solutions.
• Business Growth: Partner with cross‑functional business development and product leadership teams to identify new data opportunities, define proposals, and participate in client pitches.

Team Management & Mentorship

• People Leadership: Manage, recruit, and retain a multi‑disciplinary team of Senior Data Scientists, Machine Learning Engineers, and AI Researchers.
• Technical Guidance: Conduct deep‑dive technical reviews, architectural assessments, and model design audits to ensure production reliability, scalability, and fairness.
• Talent Development: Foster a culture of continuous learning, mentoring junior and senior staff on advanced algorithms, production ML engineering practices, and executive communication.

Technical Excellence & Operations

• End-to-End Execution: Oversee the lifecycle of data products from discovery, exploratory data analysis (EDA), prototyping, to production deployment (MLOps) and monitoring.
• Best Practices & Governance: Establish enterprise‑grade frameworks for model governance, ethical AI practices, data quality assurance, and code reproducibility.
• R&D & Innovation: Stay ahead of industry trends, evaluating and integrating emerging technologies in Generative AI, Large Language Models (LLMs), deep learning, and scalable cloud ML platforms.