Tech Innovation - UX Researcher - Remote Infomineo

About this role:

We are builders and learners at heart. At BRAIN, you ll help shape what we build. We combine clear data, solid engineering, and thoughtful design to solve real problems.

• Impact from Day One: We don't believe in "busy work." Whether you are building features, deploying infrastructure or researching user needs, your work will directly shape live products and real business outcomes.
• A Culture of Experimentation: We embrace the scientific method in everything we do. We build, we measure, we learn, and we iterate. Failure isn't punished; it's data for the next breakthrough.
• Cutting-Edge Tech Stack: From Agentic AI and Kubernetes orchestration to advanced Statistical Modeling, you will work with the tools that define the modern tech landscape.
• Growth-Oriented Environment: We invest in your potential. You will have mentorship from senior leaders and the autonomy to grow into technical and non technical leadership roles.
• Agile & Collaborative: We work in fast-paced sprints where engineering, design, and product sit at the same table.

We are seeking a data-driven and design-thinking oriented UX Researcher to join our Product team. This role operates at the intersection of discovery, validation, and design. You will not only analyze the "why" and "what," but you will also actively shape the solution.

You will be responsible for end-to-end product validation: from facilitating Design Sprints to uncover needs, to prototyping solutions, and finally using rigorous statistical methods to prioritize features. You will be the bridge between user needs, business strategy and the development teams, ensuring we only build what is validated and high-value.

Who you are?

1.Innovation & Product Design

• Plan and Execute Design Sprints: Lead cross-functional Design Sprints or Venture Design sprints. You will guide the cross functional teams through mapping user journeys, sketching solutions, and deciding on the MVP.
• Identify Needs & Solutions: Facilitate workshops to identify deep user pain points and unmet needs. You are expected to move beyond problem identification and propose tangible solutions to tackle them.
• Strategy Alignment: Ensure that sprint outcomes align with the broader company goals and business viability.

2. Prototyping & Pre-Development Validation

• Prototype & Iterate: Create low-to-mid fidelity prototypes (wireframes, click-throughs) to visualize potential solutions immediately following discovery sessions.
• Validate Before Execution: Conduct iterative testing on these prototypes to validate ideas before development begins. You will be the gatekeeper who ensures engineering resources are not wasted on unproven concepts.
• Rapid Feedback Loops: Set up quick feedback mechanisms to iterate on product design daily or weekly based on user inputs.

3. Statistical Analysis & Feature Prioritization

• Feature Prioritization: Design and deploy quantitative surveys specifically aimed at understanding feature and product attribute priorities. You will answer: "Which feature drives the most value?" and "What is the optimal product configuration?"
• Advanced Methodologies: Utilize methodologies such as Conjoint Analysis, MaxDiff, and Kano Modeling to rank user preferences scientifically.
• Inferential Statistics: Apply inferential statistics to validate findings. You will be responsible for calculating statistical significance, confidence intervals, and effect sizes.
• Technical Rigor: Determine if a result is significant (e.g., $p

4. Cross-Functional Collaboration

• Partner with Product and Development teams to marry log data with attitudinal survey data.
• Work closely with Product Managers to translate quantitative insights into actionable improvements.
• Democratize data by creating accessible dashboards and reports for stakeholders.

Who you are?

• Education & Experience
• Education: Degree in Statistics, Marketing or a related field.
• Experience: 2-5 years of experience within product teams.
• Technical, Statistical & Design Proficiency
• Prototyping Tools: Proficiency in Figma, or similar tools to create testable artifacts.
• Statistical Tools: Proficiency in Python (pandas, NumPy, SciPy), R or SPSS.
• Statistical Knowledge: Proficiency and understanding of parametric and non-parametric statistical tests.
• Survey Platforms: Proficiency with tools like Qualtrics, SurveyMonkey, Typeform or other similar tools.
• Data Manipulation: SQL skills to query databases and build dashboards.
• Soft Skills
• Facilitation: Strong ability to command a room, guide stakeholders through ambiguity, and run productive Design Sprints.
• Data Storytelling: The ability to translate statistical concepts into clear, human-centric narratives that aid decision making.
• Critical Thinking: A healthy skepticism of data. You know when data is "dirty" and how to check for bias.