United Kingdom
Senior data scientist blending psychology and technology to craft innovative AI solutions. I specialize in integrating LLMs with psychometric data, creating systems that enhance engagement while championing responsible innovation. Thriving at the crossroads of art and science, I find creative solutions to intricate problems. Skilled in Python, R, SQL, and NLP, I'm driven by a passion for developing systems that simplify complex insights through intuitive design. Balancing technical skill with practical business impact, I mentor junior scientists and collaborate across teams to turn data into actionable solutions. With a background in cognitive neuroscience and a deep understanding of how people think and work, I believe the most impactful technology understands people, not just data. This is why I specialize in making complexity and depth feel intuitive by merging psychology and technology. From exploring emotional responses to music to developing ethical assistants that make psychological data accessible through natural language, I'm captivated by the patterns that define us as humans. Always curious about the 'why' behind the numbers, I'm dedicated to building AI that truly serves people.
-Drive innovation by designing, developing, and testing impactful AI solutions, leading exploratory projects, and identifying opportunities for competitive differentiation through AI. -Champion continuous learning by staying updated on AI advancements, advocating for ethical AI practices, and driving widespread AI adoption across the organization. -Mentor and develop junior data scientists, fostering a culture of innovation, continuous learning, and overcoming technical challenges. -Represent Thomas as a thought leader by sharing AI insights, collaborating with stakeholders, advocating for ethical AI practices, and showcasing expertise at industry events.
Role and Responsibilities -Apply data science principles and understand best practice in terms of deriving insights -Define data requirements (tooling, methods, and principles) in order to strategically apply analytics to wider business questions -Develop strategy for projects that help drive product value for customers -Represent data science in cross-function projects by articulating the data requirements of a project as well as scoping timelines to ensure projects are delivered to a high standard