We are hiring a Process Analytics Consultant to support initiatives across multiple business domains, helping teams improve operational performance through process analytics, process discovery, and process optimisation.
A core part of this role involves supporting research and applied experimentation by developing, testing, and refining approaches to process discovery and optimisation using data-driven methods. The consultant will work with stakeholders across business and technology teams to structure problem statements, analyse workflow behaviour from data, and produce insights that translate into practical improvements and scalable solutions.
In addition, the consultant may contribute to adjacent delivery workstreams such as data engineering, dashboarding, and UI/UX design to help operationalise insights into usable tools, products, or internal platforms.
This role spans multiple disciplines. Candidates are not expected to be experts in everything. We are looking for individuals with strong capability in one or two areas (e.g., process analytics / process mining, data engineering, research) and working-level proficiency across the rest, with the ability to collaborate and execute in a cross-functional team.
Key Responsibilities
1) Process Analytics \& Cross-Domain Insights (Core Focus)
Analyse workflows across different business domains to identify inefficiencies, delays, bottlenecks, rework loops, and manual pain points
Support end-to-end process understanding using operational data (e.g., event timestamps, transaction records, system logs)
Define and track process performance metrics such as cycle time, throughput, SLA adherence, exception rates, and handoff delays
Translate analytical findings into clear improvement opportunities, prioritised recommendations, and measurable outcomes
Partner with stakeholders to validate findings, align on process realities, and drive adoption of recommendations
2) Research Support: Process Discovery \& Process Optimisation (Major Component)
Support research initiatives related to process discovery and process optimisation, including structured experimentation and evaluation
Explore and compare methods for uncovering process flows from data (e.g., event sequences, data relationships, heuristics)
Assist in prototyping approaches, evaluating output quality, and documenting findings clearly
Produce research-driven deliverables such as technical notes, experiment results, and implementation recommendations
Contribute to improving repeatability and scalability of process analytics methods (e.g., reusable frameworks, templates, pipelines)
3) Data Engineering Enablement (Supporting Workstream)
Support data extraction and preparation needed to enable process analytics and research initiatives
Assist with data modelling, transformation, quality checks, and data validation to ensure usable analytics outputs
Help define data requirements and improve access to reliable process-related datasets
Contribute to building lightweight pipelines or curated datasets that reduce manual effort over time
4) Dashboarding \& Insight Delivery (Supporting Workstream)
Build or support dashboards and analytical views to communicate process performance and operational insights
Convert process metrics into stakeholder-friendly reporting, monitoring views, and decision-support dashboards
Partner with stakeholders to iterate on dashboards to ensure usability, clarity, and relevance
5) Data Governance \& Business Architecture Support (Supporting Workstream)
Support data governance initiatives linked to process analytics, including:
improving data definitions and consistency
supporting ownership / stewardship clarity
identifying data quality gaps impacting process insights
Assist in mapping process-to-system and process-to-data relationships to improve transparency and traceability
Contribute to business architecture artefacts such as:
business capability mapping
workflow documentation and operating model views
alignment between business processes and enabling applications
6) UI/UX \& Tooling Support (Supporting Workstream)
Contribute to UI/UX design improvements to help operationalise process insights into intuitive tools
Support the design of user workflows, wireframes, and lightweight prototypes where needed
Collaborate with engineers / developers / product owners to ensure solutions are usable, adoption-friendly, and scalable
7) Stakeholder Engagement \& Delivery Execution
Work directly with business and technology teams to gather requirements, clarify problems, and structure delivery plans
Communicate progress through clear documentation, working sessions, and stakeholder updates
Support delivery across multiple workstreams in a fast-moving innovation environment
Skills Required
A) Core Skills
Demonstrate strong analytical thinking \& structured problem-solving
Process analytics mindset: ability to reason about bottlenecks, cycle times, handoffs, rework, and exceptions
Strong stakeholder management \& communication across business and technology teams
High-quality documentation skills (clear findings, assumptions, definitions, recommendations)
High resilience and execution under pressure: able to operate in ambiguity, handle shifting priorities, and deliver in demanding environments
B) Technical Skills
These are required for the role:
Strong SQL (data extraction, joins across multiple tables, aggregations, performance-aware querying)
Strong Python (data wrangling, analysis, prototyping, and building repeatable analytical workflows)
Comfort working with complex operational datasets (timestamps, events, transaction/activity data)
C) Process Analytics \& Research Skills (Strongly Preferred / Core Differentiator)
Experience in process discovery and/or process optimisation
Strong research capability: ability to run structured experiments, compare approaches, and document results clearly
Familiarity with concepts such as:
event sequences / timestamp-based analysis
process performance measurement and KPIs
workflow variability and exception patterns
process mining / discovery methods (tool-based or custom)
D) Supporting Skills (Preferred / Plus)
Candidates are not expected to be strong in everything below. Strong capability in 1–2 areas + working knowledge in the rest is ideal.
Dashboarding / BI Tools (Plus)
Exposure to Tableau, Power BI, or similar dashboarding tools
Ability to convert process metrics into stakeholder-friendly monitoring views and dashboards
Low-Code / Automation Exposure (Plus)
Exposure to Power Apps / Power Automate (or similar tooling)
Understanding of basic automation concepts (workflow triggers, exception handling, controls)
UI/UX \& Front-End (Great to Have)
Experience contributing to UI/UX design for internal tools
React (or equivalent) experience is a strong plus, especially if you can build usable prototypes quickly
E) Data Governance \& Business Architecture Knowledge (Preferred)
Working knowledge of data governance fundamentals:
metadata / definitions
ownership \& stewardship
data quality considerations
Awareness of business architecture concepts:
business capability mapping
process-to-system and process-to-data mapping
operating model documentation
F) Preferred Qualifications
Master’s or PhD in Computer Science / Data Science / Information Systems / related discipline required
Candidates with academic research experience (publications, thesis, experimentation-heavy projects) will be viewed favourably
Compensation / Rate
SGD 8,000 – 14,000 per month, depending on experience and skill depth
Final rate will be calibrated based on strength in process analytics / process discovery research, and hands-on capability in SQL + Python, or Data Engineering and other above mentioned domain knowledge.
Find out more about what we do at https://tessely.ai/
Job Types: Full-time, Permanent, Contract
Contract length: 24 months
Pay: $8,000.00 - $12,000.00 per month
Benefits:
Additional leave
Flexible schedule
Professional development
Unlimited paid time off
Work from home
Education:
Bachelor's or equivalent (Required)
Work Location: Hybrid remote in Singapore 159948