Technical Product Manager

KBC Technologies Group
Edinburgh
6 months ago
Applications closed

Related Jobs

View all jobs

Machine Learning Manager

Product Specialist Graduate Level

Contract Python Software Engineer - Trading

Software Engineer - ML Developer Tools

AI Scientist

Design & Development Engineer (Hardware)

Job Summary:

We are currently looking for a Senior Product Manager to grow our product capability and help our clients in the financial services sector build great products. Technical knowledge and a robust engineering background is preferable but not mandatory. Candidates should have a proven track record of delivering high-impact products within the retail BFSI sector. This role demands a dynamic leader adept at blending strategic vision with profound technical expertise to spearhead the development and market introduction of flagship products. Ideal candidates will have experience launching mass-market, complex, customer-centric, finance applications at scale.


Responsibilities:

  • Product Leadership: Define and execute the product vision and strategy, ensuring alignment with business objectives and market needs. Lead the development and launch of innovative features that significantly enhance user engagement and satisfaction.
  • Engineering Collaboration: Collaborate closely with engineering teams to architect and design technically excellent and commercially viable solutions. Ensure the development of robust, scalable, and innovative products.
  • Data-Driven Decision Making: Utilize analytics and user feedback to inform product decisions. Implement strategies that result in measurable improvements in user engagement, revenue, and retention.
  • Cross-Functional Team Management: Lead and work alongside cross-functional teams, including engineering, design, marketing, and sales, to deliver seamless product experiences. Enhance team productivity and collaboration through effective leadership and mentoring.
  • Market Insight: Conduct comprehensive market research and competitor analysis to anticipate industry trends and strategically position our products. Develop partnerships that enhance product offerings and market presence.


Critical Domain Experience:

Retail Experience in BFSI: Extensive experience managing product lines within the BFSI retail sector at scale is required. A deep understanding of customer needs, expectations, and regulatory requirements in this sector is crucial.

Key Success Factors/Metrics:

User Engagement: Increase in active users, session length, and frequency of use.

Revenue Growth: Direct contribution to revenue through new features and enhancements.

Customer Satisfaction: Improvement in Net Promoter Score (NPS) and customer satisfaction ratings.

Time to Market: Reduction in time from concept to launch.

Team Productivity: Increase in delivery efficiency and cross-functional team collaboration.

Qualifications:

  • Experience: 10+ years product experience at global FinTech, bank or comparable data delivery or consumption company with client exposure. Previous leadership roles in product management at major tech firms preferred.
  • Industry/Domain experience and expertise within at least one of Capital Markets, Retail Banking & Payments or Wealth & Asset Management.
  • Minimum of 3 years of involvement in business-to-consumer capital markets technology


Education:Master’s degree in Management or Computer Science Engineering, or a related field from a prestigious institution.

Technical Skills:Advanced understanding of software engineering, system architecture, and Agile development processes. Proficiency in DevOps, machine learning, AI, and hardware/software integration is optional

Soft Skills:Excellent negotiation, communication, and stakeholder management skills. Strong analytical, decision-making, and problem-solving abilities.


Critical SFIA Skills Model for this Role:

  • Enterprise and Business Architecture (STPL, Level 6): Provides overall direction in strategic planning and policy development. Has a deep understanding of technological trends and advancements.
  • Product Management (PROD, Level 6): Initiates the creation of new products and services. Identifies how developing new products or adapting existing products can new opportunities. Champions the importance and value of product management principles and appropriate product development models.
  • Stakeholder relationship management (RLMT, Level 5): Builds long-term, strategic relationships with senior stakeholders (internal and external). Negotiates to ensure that stakeholders understand and agree on what will meet their needs, and that appropriate agreements are defined.
  • Innovation (INOV, level 5): Leads the communication and an open flow of creative ideas between interested parties and the set-up of innovation networks and communities.
  • Consultancy (CNSL, level 5): Enhances the capabilities and effectiveness of clients, by ensuring that proposed solutions are fully understood and appropriately exploited.
  • Demand management (DEMM, level 6): Engages with and influences senior stakeholders to improve the business value delivered from new or existing services and products.

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

10 Ways AI Pros Stay Inspired: Boost Creativity with Side Projects, Hackathons & More

In the rapidly evolving world of Artificial Intelligence (AI), creativity and innovation are critical. AI professionals—whether data scientists, machine learning engineers, or research scientists—must constantly rejuvenate their thinking to solve complex challenges. But how exactly do these experts stay energised and creative in their work? The answer often lies in a combination of strategic habits, side projects, hackathons, Kaggle competitions, reading the latest research, and consciously stepping out of comfort zones. This article will explore why these activities are so valuable, as well as provide actionable tips for anyone looking to spark new ideas and enrich their AI career. Below, we’ll delve into tried-and-tested strategies that AI pros employ to drive innovation, foster creativity, and maintain an inspired outlook in an industry that can be both exhilarating and daunting. Whether you’re just starting your AI journey or you’re an experienced professional aiming to sharpen your skills, these insights will help you break out of ruts, discover fresh perspectives, and bring your boldest ideas to life.

Top 10 AI Career Myths Debunked: Key Facts for Aspiring Professionals

Artificial Intelligence (AI) is one of the most dynamic and rapidly growing sectors in technology today. The lure of AI-related roles continues to draw a diverse range of job seekers—from seasoned software engineers to recent graduates in fields such as mathematics, physics, or data science. Yet, despite AI’s growing prominence and accessibility, there remains a dizzying array of myths surrounding careers in this field. From ideas about requiring near-superhuman technical prowess to assumptions that machines themselves will replace these jobs, the stories we hear sometimes do more harm than good. In reality, the AI job market offers far more opportunities than the alarmist headlines and misconceptions might suggest. Here at ArtificialIntelligenceJobs.co.uk, we witness firsthand the myriad roles, backgrounds, and success stories that drive the industry forward. In this blog post, we aim to separate fact from fiction—taking the most pervasive myths about AI careers and debunking them with clear, evidence-based insights. Whether you are an established professional considering a career pivot into data science, or a student uncertain about whether AI is the right path, this article will help you gain a realistic perspective on what AI careers entail. Let’s uncover the truth behind the most common myths and discover the actual opportunities and realities you can expect in this vibrant sector.

Global vs. Local: Comparing the UK AI Job Market to International Landscapes

How to navigate salaries, opportunities, and work culture in AI across the UK, the US, Europe, and Asia Artificial Intelligence (AI) has evolved from a niche field of research to an integral component of modern industries—powering everything from chatbots and driverless cars to sophisticated data analytics in finance and healthcare. The job market for AI professionals is consequently booming, with thousands of new positions posted each month worldwide. In this blog post, we will explore how the UK’s AI job market compares to that of the United States, Europe, and Asia, delving into differences in job demand, salaries, and workplace culture. Additionally, we will provide insights for candidates considering remote or international opportunities. Whether you are a freshly qualified graduate in data science, an experienced machine learning engineer, or a professional from a parallel domain looking to transition into AI, understanding the global vs. local landscape can help you make an informed decision about your career trajectory. As the demand for artificial intelligence skills grows—and borders become more porous with hybrid and remote work—the possibilities for ambitious job-seekers are expanding exponentially. This article will offer a comprehensive look at the various regional markets, exploring how the UK fares in comparison to other major AI hubs. We’ll also suggest factors to consider when choosing where in the world to work, whether physically or remotely. By the end, you’ll have a clearer picture of the AI employment landscape, and you’ll be better prepared to carve out your own path.