Senior Applied Data Scientist

NuroTrace; Portugal; Remote; EUR 90,000 - 130,000; Full time

Job summary

NuroTrace is seeking a Senior Applied Data Scientist who will transform raw ideas into measurable, testable models. You will work with leadership to identify data needs and use statistical modelling to validate commercial and technical viability.

The role emphasizes turning ambiguity into evidence-based decisions, building production-ready code, and collaborating across CV and platform teams to drive strategic outcomes.

Qualifications

• 5+ years of hands-on experience in a commercial setting as a Data Scientist or related role.
• Proven track record applying statistical modelling and hypothesis testing to real-world problems.
• Commercial proficiency in Python, SQL, and data analysis tools with production-grade code experience.
• Experience handling incomplete or unstructured datasets in real-world environments.
• Experience in AI/ML environments and predictive modelling.
• Exposure to enterprise platforms or product strategy environments.

Responsibilities

• Hypothesis Testing: translate theories into testable models and validate with structured experiments.
• Data Structuring: organise and prepare incomplete/unstructured datasets for analysis.
• Strategic Analysis: develop predictive and mathematical models and present clear recommendations.
• Cross-Functional Collaboration: work with leadership, product and technical teams to shape decisions.

Skills

Hands-on experience

Statistical modelling

Hypothesis testing

Data storytelling

AI/ML experience

Tools

Python

SQL

CV frameworks

Job description

Job Title: Senior Applied Data Scientist

Location: Remote (Europe-based)

About NuroTrace

NuroTrace is a fast-growing technology company offering a next-generation product identity and traceability platform that helps organizations verify, track, and manage physical assets with total confidence. We develop innovative solutions designed to give businesses clearer insight, stronger protection, and smarter ways of working across their entire supply chain. As we scale, we are looking for an experienced Applied Data Scientist to join the team.

Role Overview

We are driving a key initiative focused on validating complex business and technical theories through structured analysis and modelling. This role is centred around taking raw ideas, assumptions, and internal hypotheses, often not yet clearly defined and turning them into measurable models that can be tested, challenged, and proven.

You will work closely with leadership and technical teams to structure incomplete information, identify what data is needed, and use statistical modelling to determine whether proposed ideas are commercially and technically viable.

This role requires someone who is highly analytical, comfortable working with ambiguity, and confident turning unstructured problems into clear, evidence-based decisions.

Key Responsibilities

Hypothesis Testing:

• Translate business and technical theories into testable models
• Validate assumptions using statistical methods and structured experimentation
• Assess whether proposed ideas are commercially and technically viable
• Challenge assumptions and improve decision-making through evidence-based analysis

Data Structuring:

• Work with incomplete, inconsistent, or unstructured datasets
• Build frameworks that organise data for effective analysis
• Identify missing data points and define data requirements
• Improve data quality and analytical readiness across projects

Strategic Analysis:

• Develop predictive, statistical, and mathematical models
• Support leadership with clear recommendations based on findings
• Present complex analysis in a practical and understandable way
• Help shape product, platform, and operational decisions through data insight

Cross-Functional Collaboration:

• Work closely with leadership, product, and technical teams
• Support wider platform initiatives through analytical input
• Collaborate across teams to improve decision quality and strategic planning
• Contribute to projects involving complex enterprise workflows and systems

What You Bring

• 5+ years of hands-on experience in a commercial/industry setting as a Data Scientist, Advanced Analytics professional, or in a closely related role (excluding academic, internship, or university-only research)
• Proven track record of applying statistical modelling and hypothesis testing to solve real-world business problems
• Commercial proficiency in Python, SQL, and data analysis tools with experience building clean, maintainable, production-ready code
• Demonstrated experience handling incomplete or unstructured datasets within real-world business environments
• Strong problem-solving and critical thinking skills
• Ability to explain complex findings clearly to both technical and non-technical audiences
• Experience in AI/ML environments
• Experience with predictive modelling and experimentation frameworks
• Exposure to enterprise platforms or product strategy environments
• Experience working alongside Computer Vision workflows, particularly within existing image analysis frameworks
• Familiarity with collaborating across CV-based environments and supporting visual data modelling

Key Attributes:

• Highly analytical with strong attention to detail
• Comfortable working with ambiguity and undefined problems
• Able to challenge ideas constructively and confidently
• Strong communication and stakeholder management skills
• Focused on practical outcomes and business impact

Success Criteria

• Clear validation of key internal theories and assumptions
• Improved decision-making through structured analytical insight
• Stronger use of data in strategic and technical planning
• Well-defined models supporting business and platform growth
• Effective collaboration across technical and leadership teams

Summary

This role is ideal for someone who enjoys solving complex problems, testing assumptions, and turning uncertainty into clear direction.

You will play an important role in helping the business make stronger strategic decisions by providing evidence, structure, and analytical confidence across key initiatives.