Data Scientist – ML Engineer

Location: Strong preference for candidates in the UK

Reports to: Chief Technology Officer

Engaging Networks is seeking a Data Scientist who will help define our machine learning roadmap and build on the foundations of our existing ML models. You will take the lead on the development of our ML platform, using historical transactional and behavioral data to drive strategic outcomes for our clients. This is a hands‑on role requiring the ability to move fluidly between model design and cloud deployment.

About Engaging Networks: Engaging Networks is a global software company dedicated to empowering the world’s most important causes. We provide an all-in-one fundraising, advocacy and marketing platform built specifically for nonprofits. Our integrated, easy‑to‑use technology eliminates data silos and tech headaches, helping organisations connect with supporters in smarter, more meaningful ways to drive real change.

Responsibilities:

• Architecture & Deployment: Lead the end-to-end development and testing of a Python‑based ML platform.
• Cloud Infrastructure: Architect and manage ML environments specifically within AWS (SageMaker, Lambda, S3), ensuring scalable training and deployment pipelines.
• Data Orchestration: Develop a unified data structure for our AI platform using existing and new APIs and databases.
• Hybrid Modeling: Build and deploy classifier and predictive models (e.g., churn prediction, propensity scoring) using scikit‑learn or similar. Implement modern LLM applications, including Retrieval‑Augmented Generation (RAG) and prompt engineering.
• Strategic Leadership: Collaborate with product and engineering leaders to identify high‑impact AI opportunities and make the vision a reality.
• Performance Optimization: Continuous deployment and evaluation of the platform to improve accuracy, efficacy, and prediction speed.

Requirements:

• Professional Experience: 2+ years of industry experience as a Data Scientist or ML Engineer, with a track record of moving real projects into production.
• Python Mastery: Expert‑level Python development skills, including standard libraries like NumPy, Pandas, and SciPy.
• Predictive & Deep Learning: Deep knowledge of machine learning workflows in scikit‑learn and at least one deep learning framework such as PyTorch or TensorFlow.
• Generative AI: Practical experience with LLM orchestration (e.g., LangChain) and vector databases for RAG workflows.
• Cloud & DevOps: Professional experience with AWS/SageMaker (or similar) and a strong comfort level with Linux/Unix environments.
• Data Engineering: Proficiency in SQL and experience preparing or scraping complex datasets for machine learning.
• Education: A strong background in Statistics, Mathematics, or Physical Sciences.
• Soft Skills: A meticulous attention to detail combined with the “founding hire” mindset—curious, eager to build from scratch, and interested in making change happen.
• Autonomy: Shape the AI culture and tech stack of an established company from day one.
• Flexibility: Flexible working hours and remote‑friendly locations.
• Growth: Budget to attend major sector conferences and stay at the cutting edge of AI/ML.

Compensation: The salary range for the role is £50,000 – £55,000 GBP annually and may be higher based on experience and proven abilities. Engaging Networks provides its employees with ample benefits, as well as paid vacation, paid sick days, paid parental leave, and other benefits that vary somewhat according to whether you’re located in the UK, USA or Canada. Team members worldwide benefit from an employer‑matching charitable gift program and are invited to take one extra paid vacation day each year to engage in a volunteer activity of their choosing. Women and minorities are encouraged to apply. Engaging Networks does not discriminate on the basis of race, color, religion, national origin, gender, sexual orientation, age, veteran status or disability. We strive in our hiring practices to give equal opportunity to all qualified job applicants and value diversity among our team members.