Process Intelligence Consultant

Trust in SODA; Grimsby; Remote; GBP 111,000 - 120,000; Full time

Job summary

Trust in SODA is seeking a Process Intelligence Consultant for a 2-month contract with potential extension. This remote position offers a daily rate of £600-£650 outside IR35 and starts ASAP.

You will combine deep process-mining, data analysis and business consulting to identify critical questions, investigate client operations and turn findings into practical recommendations, collaborating with data engineers and process experts.

Qualifications

• Proven process-mining consulting delivery using event data to solve business problems.
• Strong business consulting skills; structure problems and engage C-Suite stakeholders.
• Hands-on platform expertise in Celonis, QPR ProcessAnalyzer, SAP Signavio, UiPath Process Mining.
• Strong SQL and Python skills to join, transform and interrogate datasets.

Responsibilities

• Lead analytical investigations.
• Work directly in process-mining tools to build models and investigate variants.
• Connect data to business behaviour by comparing performance across units.
• Work with clients and data engineers to validate data and findings.
• Develop recommendations and business cases with quantified opportunities.
• Measure results and improve our methods with reusable analyses.

Skills

Process mining

Consulting delivery

SQL

Python

Data analysis

Stakeholder communication

Process modelling

Tools

Celonis Process Mining

QPR ProcessAnalyzer

SAP Signavio

UiPath Process Mining

Job description

Process Intelligence Consultant – Contract Position – HIRING ASAP

Location: Remote working

Start Date: ASAP

Duration: 2-month initial contract with long-term extension

Daily Rate: £600 - £650 per day outside IR35

Summary

We are looking for a Process Intelligence Consultant who combines deep technical process-mining and data analysis skills with business consulting experience. You will identify the questions worth asking, investigate client operations and turn findings into practical business recommendations, working across engagements with our professional services clients alongside data engineers and process experts.

Requirements

• Proven process-mining consulting delivery. You have personal expertise in using operational event data to investigate business problems and help clients act on your findings.
• Strong business consulting skills. Structure ambiguous problems, learn a client's value chain quickly, facilitate workshops and explain recommendations to C-Suite stakeholders.
• Substantial hands‑on platform expertise. Confident building models, queries and analyses independently in tools like Celonis, QPR ProcessAnalyzer, SAP Signavio, UiPath Process Mining or a comparable platform.
• Strong SQL and practical Python skills. Able to join, transform and interrogate operational datasets and validate the results.
• Sound process‑modelling judgement. Understand case definitions, event granularity, timestamps and data quality, including incomplete cases, parallel activity and the distinction between elapsed time and working effort.
• Commercial judgement and analytical rigour. Connect findings to business outcomes, test alternative explanations and communicate uncertainty. Produce reproducible work and handle confidential data carefully.

Responsibilities

• Lead analytical investigations. Identify business questions, formulate hypotheses and decide which analyses will produce useful answers.
• Work directly in process‑mining tools. Build analytical models, write queries and investigate process variants, delays, rework, handovers and exceptions.
• Connect data to business behaviour. Compare performance across work types, teams and organisational units, and investigate the reasons for differences.
• Work with clients and data engineers. Define data requirements, validate process models and lead client workshops to test findings against operational reality.
• Develop recommendations and business cases. Quantify opportunities to improve service, capacity, cost, working capital and control, with clear assumptions.
• Measure results and improve our methods. Establish baselines, track benefits and develop reusable analyses, contributing to ongoing process simulation work.