At a Glance
- Tasks: Lead the development of innovative analytical products and automate processes to enhance insights.
- Company: Join a forward-thinking company focused on cutting-edge technology and collaboration.
- Benefits: Enjoy competitive pay, health perks, remote work options, and growth opportunities.
- Other info: Dynamic role with opportunities for mentorship and career advancement.
- Why this job: Make a real impact by solving business challenges with AI and modern engineering techniques.
- Qualifications: Experience in analytics, software engineering, and a passion for emerging technologies.
The predicted salary is between 63000 - 77000 £ per year.
- Working within the Insight Solutions group, the Insights Tech Lead is a hands-on technical leader responsible for identifying, designing and delivering innovative analytical products that improve the efficiency, scalability and quality of Reward's insight capability
- Operating at the intersection of Insight Solutions, Analytical Engineering, Data Engineering, Software Engineering and Data Product, the role rapidly develops proof-of-concept applications, automation and configurable analytical solutions that solve real business problems
- Successful solutions are embedded within the Insight team to deliver immediate value before being transitioned into long-term business platforms through collaboration with Engineering and Product teams
- The Consumer Insights Tech Lead combines strong engineering expertise with commercial understanding to accelerate innovation, reduce manual effort, standardise analytical processes and enable Reward to deliver best-in-class client insight at scale
- Identify opportunities to improve Reward's analytical capability through automation, configurable solutions and innovative technical products
- Design, build and validate proof-of-concept applications and data products that solve business and commercial challenges
- Rapidly prototype new analytical capabilities using modern engineering techniques, cloud technologies and AI tooling
- Work closely with Insight Solutions to embed successful solutions into analyst workflows and maximize business benefits
- Partners with Engineering and Data Product teams to transition successful proof-of-concepts into scalable production solutions
- Champion the adoption of AI, automation and modern engineering practices across the Insight function
- Reduce manual effort by developing reusable frameworks, configurable analytical products and scalable automation
- Translate business requirements into robust technical solutions that improve the quality, consistency and speed of insight delivery
- Ensure all technical solutions meet high standards of accuracy, maintainability, usability and performance
- Evaluate emerging technologies and identify opportunities to enhance Reward's analytical capability and internal tooling
- Promote engineering best practice, technical documentation and knowledge sharing across teams
- Act as the technical authority within Insight Solutions, providing guidance on solution architecture, AI adoption and engineering approaches while collaborating closely with Engineering and Data Product teams
- Demonstrable experience delivering proof-of-concept applications from ideas through validation and adoption
- Experience identifying opportunities to improve operational efficiency through technology and automation
- Significant experience in Analytics Engineering, Data Engineering, Business Intelligence, Software Engineering or a similar technical discipline
- Proven experience developing enterprise analytical solutions, automation and reusable technical products
- Experience working across multidisciplinary teams including Insight, Engineering, Product and Commercial functions
- Experience working with AI technologies to accelerate software development and business capability is highly desirable
- Experience with Docker, AWS and/or Google Cloud Platform
- Advanced SQL (Amazon Redshift, T-SQL) and data modelling
- Experience developing AI applications using Large Language Models (LLMs), including prompt engineering, RAG, vector databases, embeddings and commercial AI platforms (e. g.
- Open AI, AWS Bedrock)
- Experience building scalable data products and analytics solutions
- Expert Power BI development, including semantic models and Power BI Service administration
- Expert Python development for data, analytics and automation
- Experience integrating REST APIs and multiple data sources
- Knowledge of traditional machine learning techniques, including tree-based models (e. g.
Random Forest, Cat Boost), feature engineering techniques such as TF-IDF, and experience evaluating and deploying AI/ML solutions in commercial environments
- Excellent problem-solving, communication and stakeholder management skills
- Strong software engineering practices (OOP, testing, Git, documentation)
- Understanding of modern analytics engineering and scalable solution architecture
- Experience working within agile product or engineering teams
- Passionate about continuous improvement, automation and building scalable solutions
- Naturally curious with a passion for emerging technology and innovation
- Collaborative and approachable, with a desire to enable others through technology
- Commercially minded with a focus on solving real business problems
- Pragmatic, delivery-focused and comfortable working with ambiguity
- Experience developing internal developer tools or self-service analytical products
- Experience with CI/CD pipelines
- Experience with modern Java Script frameworks such as React
- Passion for evaluating emerging technologies and identifying opportunities to improve Reward's analytical capability
- Experience mentoring technical colleagues and promoting engineering best practices
- #J-18808-Ljbffr
Insights Tech Lead in London employer: Reward
At Reward, part of the Rezolve Ai Group, we pride ourselves on fostering a collaborative and innovative work culture that empowers our employees to thrive. As a SQL Developer in the Consumer Insights team, you will benefit from hybrid working arrangements, allowing for a balanced work-life dynamic, while also having access to professional development opportunities that encourage growth and skill enhancement. Join us in the UK, where your contributions will directly impact our data management efforts and client success, making your role both meaningful and rewarding.
StudySmarter Expert Advice🤫
We think this is how you could land Insights Tech Lead in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Reward!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Insights Tech Lead at Reward.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Reward.
✨Apply Directly through Our Website
When you find a suitable opening like Insights Tech Lead at Reward, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Insights Tech Lead in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Reward, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Reward. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Reward
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Reward!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
