Data Scientist - ML Engineer

Engaging Networks
London, UK
3 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
2 years minimum
Working hours
Shift work
Job source

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Amazon S3 Cloud Computing Databases Continuous Delivery Information Engineering Data Structures DevOps Python (Programming Language) Machine Learning
+17 more
NumPy Performance Tuning Tensorflow Azure Machine Learning SciPy SQL Databases Pytorch Delivery Pipeline Large Language Models Deep Learning Generative AI Pandas Build Management AI Platforms Scikit Learn Machine Learning Operations Data Pipelines

Job description

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.

Benefits & conditions

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. #J-18808-Ljbffr

About the company

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. We’re proud to partner with nearly 400 inspiring nonprofits globally, including Amnesty International, Cancer Research UK, Save the Children, Macmillan Cancer Support, Oxfam, RSPB, PETA, Human Rights Campaign, World Wildlife Fund, Sierra Club, Humane World for Animals and Unicef Canada, providing them with the flexible tools needed to boost revenue, amplify advocacy campaigns, and transform one-time givers into lifelong donors and supporters. As a fast-growing, privately owned company, our sole focus is on the success of our clients, not on pleasing investors, venture capitalists or stockholders. This means we are answerable only to our clients and employees. This independence and commitment, combined with our focus on constant innovation, has fueled strong annual business growth averaging 20% or more. We’re more than a platform; we’re a dedicated partner to charities worldwide, with a highly rated, human-centred support team and an exceptionally high client retention rate. Join our passionate team, with main offices in London and Washington, D.C., and help us continue to deliver the technology and partnership that make a genuine difference in the world.

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