Data Scientist Monitoring & Alerting Infrastructure Location: Manchester Hybrid (Remote & Office-Based) Salary: £65-70K plus excellent benefits package Our client is a pioneering, data-driven company that has been delivering market-shaping insights to the media and research sectors for over a decade. Their cutting-edge platform empowers global brands to make smarter decisions through actionable, real-time data. As they scale their operations and enhance data governance across their ecosystem, we are now seeking a Data Scientist with experience in monitoring and alerting infrastructure. This is a pivotal hands-on role with end-to-end ownership ideal for someone who enjoys blending engineering rigour with statistical thinking in a collaborative, fast-paced environment. Key Requirements We are looking for a proactive and technically strong Data Scientist who can develop and maintain monitoring systems across distributed data pipelines and drive data quality initiatives across multiple teams and projects. Must-have skills and experience: Proficiency in Python and SQL for analytical modelling, data interrogation, and scripting Hands-on experience with PySpark and distributed data processing at scale Production deployment of statistical or machine learning models Cloud infrastructure experience, preferably with AWS Methodical problem-solving mindset with exceptional attention to detail Ability to define, scope, and independently deliver complex technical solutions Confidence working with non-technical stakeholders to define metrics and performance indicators Self-motivated, accountable, and eager to continue growing professionally Previous experience building monitoring or data quality frameworks is highly desirable Role & Responsibilities As a Data Scientist in this role, you will take the lead on designing and implementing the systems that monitor the health, reliability, and accuracy of core datasets and pipelines. Youll collaborate with cross-functional teams to define KPIs, detect anomalies, and promote best practices for scalable data governance. Your responsibilities will include: Designing and implementing monitoring and alerting systems across data platforms Collaborating with stakeholders to define relevant metrics, thresholds, and KPIs Building and maintaining production-level statistical and ML models using Python and PySpark Deploying solutions within AWS cloud infrastructure Developing scalable frameworks to support future monitoring needs across departments Investigating and resolving data anomalies and pipeline irregularities Driving data quality standards and encouraging adoption across the business Mentoring junior team members and contributing to a culture of innovation, curiosity, and rigour Ensuring compliance with internal Security, Quality, and Health & Safety policies Why Join Our Client? The company is committed to putting its people first investing in tools, training, and culture that enable long-term career development and daily impact. Youll join a team that values ownership, experimentation, and collaboration. Benefits & Perks 25 days of paid holiday plus UK bank holidays Ability to buy or sell up to 5 days annual leave after 2 years service Workplace pension scheme with employer contributions Life assurance for peace of mind Performance-based bonus scheme Cycle to Work scheme Choice of tech equipment that best suits your working style Training budget, one-to-one coaching, and ongoing development support Annual £100 home working setup allowance Opportunities to give back through charity partnerships and community initiatives Hybrid Working Model Manchester-based office with excellent public transport links, secure bike shed, and free parking Split your time between home and office, with equipment provided (desk, screen, chair) Flexible working hours to accommodate your personal needs This is an exciting opportunity to make your mark on a mission-critical capability at the heart of data operations. If you are an analytical thinker with strong coding skills and a passion for robust data systems, wed love to hear from you.