01
TRCI-26-06614
Product Analyst- Data & Risk
This contract role is one of four Product Analyst positions supporting the Data & Risk product family, with work spanning Data Enrichment product analysis and AI/ML data-labeling and quality validation. Analysts will investigate merchant and transaction data, assess product and model outputs, support testing and releases, and communicate evidence-based findings to product, engineering, data science, and operations teams. The core requirements are 3+ years in a relevant analytical or quality-focused role, strong data analysis and problem-solving skills, comfort with SQL or similar tools, familiarity with data quality and validation, and an understanding of machine-learning workflows and classification. Experience with financial-data classification, labeling, model metrics, Vertex AI or comparable platforms, and regression or migration testing is preferred. The engagement is an extendable 12-month contract in Warsaw; the description does not specify whether the work is onsite, hybrid, or remote, and the supplied experience band is 3–5 years while the description states 3+ years.
Position summary
- Location
- Poland
- Workplace
- Hybrid
- Employment
- Contract
- Experience
- Minimum 3 years and Maximum 5 years
Role overview
Why This Role Matters.
This contract role is one of four Product Analyst positions supporting the Data & Risk product family, with work spanning Data Enrichment product analysis and AI/ML data-labeling and quality validation. Analysts will investigate merchant and transaction data, assess product and model outputs, support testing and releases, and communicate evidence-based findings to product, engineering, data science, and operations teams. The core requirements are 3+ years in a relevant analytical or quality-focused role, strong data analysis and problem-solving skills, comfort with SQL or similar tools, familiarity with data quality and validation, and an understanding of machine-learning workflows and classification. Experience with financial-data classification, labeling, model metrics, Vertex AI or comparable platforms, and regression or migration testing is preferred. The engagement is an extendable 12-month contract in Warsaw; the description does not specify whether the work is onsite, hybrid, or remote, and the supplied experience band is 3–5 years while the description states 3+ years.
Your Impact
Deliver Enterprise Value
Help organisations solve complex business problems through modern technology, consulting expertise and measurable outcomes.
Collaboration
Work Across Teams
Collaborate with consultants, architects, engineers and client stakeholders throughout the project lifecycle.
Growth
Learn Continuously
Gain exposure to enterprise technologies, certifications, mentoring and real-world project experience.
Career Path
Grow With Ubique
Build a long-term consulting career with opportunities to take on greater responsibility and leadership over time.
Responsibilities
What You'll Be Doing.
Every role at Ubique contributes directly to solving meaningful business challenges for our clients.
02
Query, structure, and analyse data to identify patterns, recurring issues, inconsistencies, and opportunities for product improvement.
03
Create clear visualisations, reports, and summaries that help stakeholders understand performance, quality, progress, and priority areas.
04
Support product discovery and delivery by clarifying requirements, documenting expected behaviour, and translating feedback into structured findings.
05
Assist with testing, validation, and quality assurance activities, including validating product behaviour during releases, migrations, and changes to data-processing logic.
06
Investigate discrepancies between expected and actual product outputs and work with relevant teams to define and track resolution actions.
07
Maintain lightweight documentation of findings, quality assessments, test outcomes, decisions, and follow-up actions.
08
Label and classify transaction and merchant data used to train and improve machine learning and AI models.
09
Review and quality assure labeled datasets to ensure accuracy, consistency, completeness, and adherence to defined guidelines.
10
Validate AI-generated labels and model outputs, identifying misclassifications, edge cases, data-quality issues, and improvement opportunities.
11
Analyse model and classification performance using appropriate measures, including precision, recall, accuracy, F1 score, and confusion matrices.
12
Support validation activities for machine learning models and AI-assisted workflows, including models hosted on platforms such as Google Vertex AI.
Technology stack
Tools & Technologies.
The platforms and technologies you'll use to build modern, enterprise-grade solutions.
01
SQL
Required
02
Structured Query Language
Required
03
spreadsheets
Required
04
Excel
Required
05
dashboards
Required
06
data visualization
Required
07
large datasets
Required
08
data quality
Required
09
data validation
Required
10
business rules
Required
11
machine learning
Required
12
ML
Required
13
AI
Required
14
data labeling
Required
15
data annotation
Required
16
classification
Required
17
taxonomy
Required
18
precision
Required
19
recall
Required
20
F1 score
Required
Requirements
Skills & Experience.
We value curiosity, collaboration and continuous learning. If you don't meet every requirement but believe you can make an impact, we'd still love to hear from you.
Essential
Required Qualifications
3+ years of relevant experience in product analysis, data analysis, data quality, QA, product operations, data labeling, or a similar technology role
Strong analytical and problem-solving skills with careful attention to detail and consistency
Comfort using data analysis tools such as SQL, spreadsheets, dashboards, or comparable tools
Experience with large datasets, data-quality processes, testing, validation, or business-rule assessment
Understanding of core machine-learning concepts and workflows, including training-data quality and model validation
Familiarity with classification problems and/or data annotation, labeling, or taxonomy-based workflows
Strong written and verbal English communication and ability to collaborate with technical and non-technical stakeholders
Preferred
Nice to Have
Experience with merchant data, transaction data, categorisation systems, or financial-data classification
Experience with data labeling, annotation, model validation, or AI-assisted labeling workflows
Familiarity with precision, recall, F1 score, accuracy, and confusion matrices
Experience supporting AI, machine-learning, MLOps, or data-platform environments
Familiarity with Google Vertex AI or comparable machine-learning platforms
Experience using SQL to investigate data issues and support product or quality analysis
Experience with test planning, regression testing, migration validation, or release-quality activities
Experience translating customer feedback or operational issues into structured analysis and product recommendations
What you'll gain
More Than Just A Job.
We're committed to helping every team member grow professionally, personally and technically while working on meaningful projects.
Global Exposure
Collaborate with international clients and multicultural teams on enterprise programmes.
Continuous Learning
Expand your expertise through mentoring, certifications and hands-on project experience.
Career Growth
Take ownership, develop leadership skills and grow your consulting career over time.
Flexible Working
Hybrid and remote collaboration designed around trust and delivering exceptional outcomes.
People First
Join a supportive culture where collaboration, respect and long-term relationships come first.
Enterprise Projects
Work on meaningful technology initiatives for leading organisations across industries.
Apply
Apply for Product Analyst- Data & Risk
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