Data Science Architect

ABOUT JMAN:

JMAN Group is a fast-growing data engineering & data science consultancy. We work primarily with Private Equity Funds and their Portfolio Companies to create commercial value using Data & Artificial Intelligence. In addition, we also work with growth businesses, large corporates, multinationals, and charities.

We are headquartered in London with Offices in New York, London and Chennai. Our team of over 450 people is a unique blend of individuals with skills across commercial consulting, data science and software engineering.

We were founded by cousins Anush Newman (Co-founder & CEO) and Leo Valan (Co-founder & CTO) and have grown rapidly since 2019. In May 2023 we took a minority investment from Baird Capital and in January 2024 we opened an office in New York with the ambition of growing our US business to be as large as, if not bigger than, our European business by 2027.

Why work at JMAN:

Our vision is to ensure JMAN Group is the passport to our teams future. We want our team to go on a fast-paced, high-growth journey with us when our people want to do something else, the skills, training, exposure, and values that JMAN has instilled in them should open doors all over the world.

Current Benefits:

• Competitive annual bonus
• Market-leading private health insurance
• Regular company socials
• Annual company away days
• Extensive training opportunities

Technical Stack:

• Expertise in strategic AI road maps for project deliverables, capability building, and measuring metrics for ROI of ML initiatives.
• High-level mastery of the Modern Data Stack (GCP, Azure, AWS) and MLOps maturity models.
• Expert user of Jira and Azure DevOps for managing complex, multi-team project lifecycles.

Qualifications:

• 810+ years of experience in Data Science/Analytics.
• 3+ years of proven experience in a managerial or people-leadership role, managing multiple direct reports or sub-teams.

Key Responsibilities:

• Oversee multiple data science workstreams, ensuring project timelines and resource allocations align with global business goals.
• Act as the primary liaison between technical teams and the C-suite, translating complex AI outcomes into strategic business value.
• Define and enforce global standards for data security, privacy, and the ethical use of AI/ML.
• Develop and execute long-term data strategies that identify new revenue streams or operational efficiencies through AI.
• Mentor and guide Senior data scientists in the focus area of project management and delivery