Director of Product Management - Advanced Analytics and AI

Harri
London
1 year ago
Applications closed

Related Jobs

View all jobs

Local Gov't Housing Data Analyst Temp: West London

Data Analyst

Commercial Data Analyst

Data Analyst - Associate Director - Belfast

Digital Data Consultant, Data Engineering, Data Bricks, Part Remote

Digital Data Consultant, Data Engineering, Data Bricks, Part Remote


About Harri:

Harri is the first enterprise-ready workforce management platform built for the services vertical. The services vertical faces the greatest technological challenges that exist within the world of Human Capital Management and we believe they deserve a platform built from the ground up as a result. We have experienced a tremendous amount of growth since our 2012 inception and we have no plans on stopping that growth anytime soon. We are passionate about building a team of Service First-driven individuals who want to exceed the expectations of those who experience our brand. 

If you’re a builder, or problem solver, and love the fast pace of a startup, it’s time to meet the Harri family.


Who you are: 

As the Director of Product Management - Advanced Analytics and AI, you will own execution and evolution of our AI-driven and advanced analytics products. This role requires a deep understanding of big data, reporting, analytics, AI technologies and product management to bridge the gap between technical development and market needs. You will work closely with engineering, data science, sales, marketing, and customer success teams to ensure the delivery of AI and analytics solutions that provide tangible business value to our customers.


Key Responsibilities:

Product Execution: Execute the product strategy and roadmap for advanced analytics and AI offerings, ensuring alignment with the overall product and company vision and market trends.Market Research: Conduct market research and competitive analysis to identify trends, opportunities, and customer pain points to inform product development.Customer-Centric Solutions: Work closely with customers and stakeholders to gather feedback and understand their needs, ensuring that our AI/ML products solve real-world problems and create valueCross-Functional Leadership: Collaborate with engineering, data science, UX, and marketing teams to drive the development, launch, and iteration of AI-driven features and analytics capabilities.Product Roadmap: Own the product lifecycle from concept to launch, including defining product requirements, prioritizing features, and managing timelines for AI/analytics-related products.AI/ML Integration: Ensure the seamless integration of AI and machine learning models into our product suite, enhancing product capabilities and customer outcomes.Data-Driven Decision Making: Utilize data and analytics to inform product decisions, measure product success, and iterate on features to meet customer needs and market demands.Go-To-Market Strategy: Collaborate with product-marketing, marketing, sales, and customer success teams to create go-to-market strategies for AI/analytics products, including positioning, pricing, and messaging.Innovation Leadership: Stay current with advancements in AI, machine learning, and analytics technologies, and apply that knowledge to drive innovation within our product portfolio.Team Leadership: Mentor and lead a team of product managers specialized in AI/ML, reporting and data analysts to deliver high-impact analytics and AI projects.Advanced Analytics: Develop and oversee the creation of advanced statistical models, machine learning algorithms, and predictive analytics to optimize labor, sales and operational performance.AI Implementation: Lead the development and integration of AI and machine learning solutions into our products, improving functionality and customer experience.Data Strategy: Collaborate with executive leadership to define data strategy, including data governance, architecture, and infrastructure, ensuring data quality and accessibility across the organization.Sales and Business Data Expertise: Leverage expertise in sales forecasting, point of sales (POS) data, inventory data, and business data models to enhance product offerings and meet customer needs within the service and hospitality industries.Vendor Management: Evaluate and manage relationships with external AI and analytics vendors to bring best-in-class tools and solutions to the organization.


Experience and Skills:

Education: Bachelor’s degree in Computer Science, Data Science, Engineering, Business, or a related field. A Master’s degree or MBA is a plus.Experience: 5+ years of experience in product management, with at least 2 years in AI, machine learning, or advanced analytics-driven products.Technical Understanding: Strong understanding of AI, machine learning, and data analytics technologies and their applications in SaaS products.Product Leadership: Proven experience leading the end-to-end product development lifecycle, from ideation to launch, with a track record of successfully delivering complex AI/analytics features.Business Acumen: Ability to translate technical capabilities into customer value propositions and business outcomes.Sales and Inventory Data Experience: Deep understanding of sales forecasting models, point of sales data analysis, inventory management systems, and how these interact with business data models to drive performance in service-driven industries.Communication: Strong communication and presentation skills, with the ability to convey complex technical concepts to both technical and non-technical stakeholders.Collaboration: Experience working cross-functionally with engineering, design, data science, and sales teams in a fast-paced, Agile environment.Customer Focus: Deep empathy for customer needs and a passion for solving customer problems with innovative AI and data-driven solutions.Analytical Thinking: Strong analytical and problem-solving skills, with a data-driven approach to decision making and product optimization.Leadership: Experience managing and mentoring product managers, fostering a collaborative, high-performance culture.


Preferred: 

Experience in SaaS platforms or with enterprise-grade products.Hands-on experience with AI/ML model deployment, natural language processing (NLP), or advanced analytics platforms.Experience with data visualization tools like ThoughtSpot, SisenseTableau, Power BI, or Looker.Knowledge in service industry products, with a focus on hospitality and related verticals.Experience building or managing products designed for the hospitality sector is a strong plus.


*Please note this job description is not designed to cover or contain a complete listing of activities, duties or responsibilities that are required of the employee for this position. Duties, responsibilities and activities may change at any time.*



Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Careers

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

Jobs

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

Careers Jobs

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.