Product Data Analyst

Background 

At Motion Applied - Connected Intelligence (CI), we create cutting-edge wireless connectivity solutions that are transforming customer experience across the transport industry. We create solutions that improve service effectiveness and cost-efficiency for customers, delivering high-quality internet connectivity services. 

By applying our expertise, we deliver real benefits and pioneer a better future. 

Purpose of the Role 

You will investigate data from our connectivity products and live operations to identify patterns, define reliable analytical logic and help convert evidence into product features and automation. Your work will move beyond one-off reporting: you will create reusable measures, definitions, classifications and validation cases that software and data engineers can implement, test and operate in production. 

You will work across telemetry, network, location, device, service-performance and commercial data. You will turn loosely defined product or operational questions into measurable hypotheses and repeatable analyses, establishing what data, transformations and quality controls are required. 

Working with Product Managers, Systems Engineers, Software Engineers and Data Engineers, you will define and validate analytical logic. Data Engineers will provide or productionise data assets where appropriate, while you will own the analytical definition, evidence, test approach and refinement of the logic. 

You will use deterministic rules where reliability, explainability and repeatability are required, and apply statistical, machine-learning or large language model approaches only where they add demonstrable value and can be appropriately validated. 

Principal Accountabilities

Investigate and structure new product insights

• Explore telemetry, network, location, device, operational and commercial datasets to identify useful patterns, behaviours, anomalies and product opportunities. 

• Turn ambiguous stakeholder questions into measurable definitions, testable hypotheses and repeatable analytical methods. 

• Assess data availability, quality, lineage and limitations, and define any additional data, transformations or reference datasets required. 

• Clean, combine and validate data from multiple sources, documenting assumptions, definitions and methods so results are traceable and reproducible. 

• Produce evidence and analytical logic that can be reused in products and operational processes, rather than only in presentations, dashboards or static reports.

Convert findings into deterministic product logic

• Define the clear sequence from source data, to metric or classification, to observed event or behaviour, to a deterministic rule or product response. 

• Specify thresholds, exceptions, precedence, confidence measures, edge cases and validation criteria clearly enough for engineering teams to implement and test. 

• Compare candidate rules or models against historical and live operational outcomes, quantifying false positives, false negatives and areas of uncertainty where appropriate. 

• Distinguish between deterministic logic, statistical inference, machine learning and LLM-based approaches, selecting the simplest reliable method that meets the need. 

• Use AI-assisted analytics and LLMs responsibly where they add value, without substituting generated outputs for reliable rules, evidence, traceability or validation.

Enable product features and automation

• Work with Product Managers, Systems Engineers and Software Engineers to convert validated analytical concepts into product requirements, acceptance criteria and test cases. 

• Create reusable definitions, classifications, calculations and reference logic that can be maintained as governed product assets. 

• Support engineering during implementation by clarifying logic, validating outputs and refining rules using representative data. 

• Help develop analytics-driven capabilities such as fault detection, service optimisation, operational alerts, coverage analysis and automated recommendations. 

• Monitor implemented logic against real-world outcomes and recommend controlled changes when performance, operating context or available data changes.

Communicate and collaborate

• Present findings clearly to technical and non-technical audiences, separating evidence, assumptions, interpretation and recommendation. 

• Explain analytical limitations and trade-offs and recommend practical next steps where the evidence supports them. 

• Contribute analytical artefacts within version control and participate in peer review, agile delivery and cross-functional product discovery. 

• Promote responsible use of data, including appropriate consideration of privacy, governance, security and customer commitments. 

Location 

This role is based at our head office in central Woking. The role is included in our hybrid working policy, with the expectation of a minimum of two days a week in the office, coordinated with other members of the Engineering team. 

Basic Qualifications and Experience 

• Bachelor's degree in a numerate discipline such as Mathematics, Physics, Computer Science, Statistics, Engineering or Economics, or equivalent practical experience. 

• Experience using data to investigate real-world product, engineering or operational problems. 

• Proficiency in SQL and confidence working with relational or analytical datasets. 

• Working knowledge of Python or another analytical language, including relevant data analysis libraries. 

• Experience cleaning, joining, validating and interpreting data from multiple sources. 

• Experience turning loosely defined questions into measurable definitions, repeatable analyses and documented conclusions. 

• Ability to define metrics, classifications, rules or thresholds and explain how they should be validated. 

• Ability to communicate analytical findings and limitations clearly to technical and non-technical audiences. 

• Ability to write and speak English fluently. 

Desirable Experience and Development Areas 

• Experience analysing telemetry, IoT, communications, networking, geospatial, time-series or event-based data. 

• Experience defining analytical rules, classifications or algorithms that have subsequently been implemented in production systems. 

• Experience with a visualisation or business-intelligence tool such as Power BI, Tableau, QuickSight or an equivalent platform. 

• Familiarity with cloud data platforms and services, particularly AWS. 

• Experience validating rules or models against real-world outcomes, including false-positive and false-negative analysis. 

• Understanding of deterministic logic, statistical methods, optimisation, machine learning and when each is appropriate. 

• Experience using AI-assisted analytics tools or LLMs responsibly, including evaluation and validation of generated outputs. 

• Experience with version control, reproducible analysis, automated testing or peer review of analytical work. 

• Understanding of data quality, data governance, privacy, security and responsible use of data. 

• Experience contributing within agile or lean cross-functional product teams. 

What Success Looks Like 

• Product and operational questions are converted into clear, measurable definitions and repeatable analyses. 

• Analytical findings are supported by traceable evidence and explicit assumptions. 

• Rules, thresholds and validation cases are sufficiently clear for engineering implementation and test. 

• Reusable analytical assets and product logic reduce reliance on one-off reports and manual interpretation. 

• Implemented features continue to be validated against real-world outcomes and refined through controlled change. 

General Requirements 

All employees must ensure compliance with the Company Health and Safety Policy and all relevant statutory Health and Safety legislation. 

This job description may not detail all duties allocated to the post holder, nor cover duties of a similar nature that are commensurate with the role and may from time to time be reasonably required by the relevant manager. 

Motion Applied is committed to Diversity, Equality and Inclusion (DEI) and promotes DEI in all we do. Motion Applied is also a member of the UK Government Disability Confident Scheme