Data Analyst: Prospect UI Solutions (Remote)

📍 Job Overview

Job Title: Data Analyst: Prospect UI Solutions Company: Constructor Location: Mexico Job Type: FULL_TIME Category: Revenue Operations / Sales Operations Support Date Posted: 2025-09-22T10:15:09.958 Experience Level: Mid-Level (2-5 years) Remote Status: Fully Remote

🚀 Role Summary

• Support Sales and Account Executive (AE) teams by developing and maintaining analytical tools and dashboards to enhance prospect demonstrations and drive pipeline velocity.
• Collaborate cross-functionally with Sales, Engineering, and Product teams to fine-tune AI models, ensuring optimal performance and relevance for prospective clients in the e-commerce sector.
• Utilize advanced data analysis techniques in SQL and Python to explore user behavior, identify product improvement opportunities, and contribute to the strategic direction of search and recommendation systems.
• Act as a key contributor in translating complex business needs into technical requirements and vice versa, facilitating effective communication and decision-making across diverse teams.
• Champion team culture by actively participating in and promoting community-building activities, fostering a supportive environment focused on empathy, personal growth, and continuous improvement.

📝 Enhancement Note: While the title is "Data Analyst," the core responsibilities and collaboration with Account Executives and Frontend Engineers to "seal the deal" strongly indicate a role deeply embedded within Sales Operations or a Revenue Operations function, specifically focused on enabling the sales process through data and analytics. The emphasis on "Prospect UI Solutions" suggests a direct impact on the pre-sales customer experience and conversion rates.

📈 Primary Responsibilities

• Design, develop, and deploy interactive dashboards and analytical tools using BI tooling for Account Executives (AEs) to improve the quality and impact of customer demonstrations.
• Conduct in-depth exploratory data analysis (EDA) using Python (pandas, NumPy, visualization libraries) and SQL to identify key trends, patterns, and insights into customer behavior and AI model performance.
• Collaborate closely with AEs to understand prospect-specific needs and fine-tune AI models, ensuring they are optimized for relevant results and maximum impact during sales cycles.
• Partner with Frontend Engineers and AEs to analyze prospect engagement with demo environments, providing data-driven feedback to support deal closure and revenue generation.
• Proactively explore large datasets to uncover opportunities for enhancing Constructor's core search and recommendation AI models, translating findings into actionable product improvement suggestions.
• Develop and maintain effective communication tools and reports to clearly articulate business performance, key metrics, and data-driven insights to both technical and non-technical stakeholders across the organization.
• Actively contribute to fostering a positive team culture through participation in team-building activities, promoting empathy, and supporting the professional growth of colleagues.

📝 Enhancement Note: The responsibilities highlight a dual focus on direct sales enablement (dashboards for demos, AI model tuning for prospects) and broader product analytics (user behavior, recommendation system improvements). This blend is typical of roles that bridge Sales Operations and Product Operations, aiming to improve both the sales funnel and the product itself based on real-world usage and prospect interactions.

🎓 Skills & Qualifications

Education:

• Bachelor's degree in a quantitative field such as Computer Science, Statistics, Economics, Mathematics, Engineering, or a related discipline. A strong academic record in data analysis and statistical modeling is highly valued.

Experience:

• Minimum of three (3) years of professional experience in a data analysis, business intelligence, or analytics-focused role, preferably within a SaaS, e-commerce, or technology environment.
• Proven experience in supporting sales, account management, or customer success teams through data-driven insights and tool development.

Required Skills:

• Proficiency in SQL: Ability to write complex queries, perform data extraction, transformation, and loading (ETL) for analysis across various database systems.
• Expertise in Python for Data Analysis: Strong command of Python libraries such as pandas, NumPy, and data visualization tools (e.g., Matplotlib, Seaborn) for exploratory data analysis and insight generation.
• Business Intelligence (BI) Tooling: Demonstrated ability to use BI platforms (e.g., Tableau, Looker, Power BI, or similar) for data analysis, dashboard creation, and reporting for both technical and non-technical audiences.
• Excellent Communication Skills: Proven ability to translate complex technical findings and business requirements into clear, concise language for diverse stakeholders, both verbally and in writing.
• Problem-Solving Acumen: Strong analytical and critical thinking skills to identify issues, develop hypotheses, and implement data-driven solutions.
• Time Management & Prioritization: Demonstrated ability to manage multiple tasks simultaneously, effectively prioritize workloads, and meet deadlines in a fast-paced environment.
• E-commerce Domain Knowledge: Familiarity with e-commerce concepts, metrics, and the typical challenges faced by online retailers is highly advantageous.

Preferred Skills:

• Big Data Stack Familiarity: Practical experience with big data technologies such as Spark, Presto/Athena, or Hive.
• Fast Prototyping: Ability to quickly develop and iterate on analytical tools and models to meet evolving business needs.
• AI Model Understanding: Basic understanding or experience working with AI/ML models, particularly in the context of personalization, search, or recommendations.
• Cross-functional Collaboration: Experience working effectively with engineering, product management, and sales teams.
• English Proficiency: C1 level (CEFR) or higher, as team collaboration and documentation will be primarily in English.

📝 Enhancement Note: The emphasis on supporting Account Executives with demos and tuning AI models for prospects places this role firmly within a GTM Operations or Sales Operations context, requiring strong analytical skills applied directly to revenue-generating activities. The "Prospect UI Solutions" aspect suggests a need for understanding user experience principles as they relate to sales tools and demonstrations.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• BI Dashboard Examples: Showcase dashboards created for sales teams, AEs, or marketing, demonstrating clear visualization of key performance indicators (KPIs), pipeline health, or demo effectiveness. Focus on interactivity and ease of use for non-technical users.
• SQL Query Performance: Include examples of complex SQL queries used for data extraction, transformation, or analysis, highlighting efficiency and accuracy.
• Python Analysis Projects: Demonstrate projects involving exploratory data analysis, data cleaning, feature engineering, or building predictive models using Python (pandas, NumPy, scikit-learn). Clearly articulate the problem, methodology, and outcomes.
• Process Improvement Case Studies: Present a documented process that was analyzed, improved, and measured for impact. This could involve sales process efficiency, demo workflow optimization, or data quality enhancement.
• Metrics & ROI Demonstration: Evidence of how your analytical work has directly contributed to measurable business outcomes, such as improved conversion rates, increased demo engagement, or enhanced AI model performance.

Process Documentation:

• Workflow Design & Optimization: Provide examples of how you have documented and optimized existing workflows, such as the sales demo process, data ingestion pipelines, or reporting procedures, to improve efficiency and reduce errors.
• Implementation & Automation: Showcase instances where you have implemented new analytical tools, automated reporting processes, or integrated different systems to streamline operations.
• Measurement & Performance Analysis: Demonstrate your ability to define relevant metrics, track performance against goals, and analyze results to drive continuous improvement in operations and sales processes.

📝 Enhancement Note: Candidates should prepare to showcase projects that directly impacted sales enablement, demo effectiveness, or AI model performance for prospects. Demonstrating the ability to translate business needs into analytical solutions and clearly communicate the resulting business value is critical.

💵 Compensation & Benefits

Salary Range: $80,000 - $120,000 USD per year. Note: The final offer will depend on factors such as job-related knowledge, skills, experience, and interview performance.

Benefits:

• Unlimited Vacation Time: Encourages employees to take at least 3 weeks per year, promoting work-life balance.
• Fully Remote Team: Offers the flexibility to work from any location.
• Work From Home Stipend: Provides resources to set up an optimal home office environment.
• Apple Laptops Provided: Ensures employees have reliable and efficient technology.
• Training and Development Budget: Annual budget for each employee to pursue professional growth and skill enhancement.
• Maternity & Paternity Leave: Support for new parents.
• Meaningful Impact: Opportunity to work with experienced professionals and contribute to significant projects.
• Regular Team Offsites: Facilitates in-person connection and collaboration among remote team members.

Working Hours:

• Employees are expected to work between 7 am and 3 pm Pacific Time (PT) to support the needs of the US-based sales team. This translates to approximately 40 hours per week, with flexibility within those core hours.

📝 Enhancement Note: The salary range is competitive for a mid-level Data Analyst role, especially in a remote capacity supporting a US-based company. The benefits package is robust, emphasizing work-life balance, professional development, and a supportive remote work environment, all of which are attractive to operations professionals. The specific PT working hours requirement is crucial for candidates to consider for timezone alignment.

🎯 Team & Company Context

🏢 Company Culture

Industry: E-commerce Technology / Artificial Intelligence (AI) / SaaS Company Size: Constructor is a U.S.-based company founded in 2019, with Engineering as its largest department. While an exact employee count isn't provided, the scale of operations (1 billion+ queries daily) suggests a significant and rapidly growing organization. Founded: 2019 by Eli Finkelshteyn and Dan McCormick.

Team Structure:

• Engineering-Centric: Engineering is the largest department, indicating a strong technical foundation and a culture that values deep problem-solving and innovation.
• Cross-Functional Collaboration: The role requires close collaboration with Account Executives (Sales), Frontend Engineers (Engineering), and likely Product Managers, emphasizing a matrixed and interdependent team structure.
• Remote-First: The team operates entirely remotely, requiring strong communication protocols and asynchronous work practices.

Methodology:

• AI & Machine Learning Driven: The company's core product is built on proprietary AI, transformers, and generative LLMs, suggesting a data-driven and technically sophisticated approach to problem-solving.
• Metrics-Focused: Constructor explicitly optimizes for revenue, conversion rate, and profit, indicating a results-oriented culture that values measurable outcomes and A/B testing.
• Continuous Improvement: The company values continuous improvement, suggesting a culture that is open to experimentation, learning from failures, and iterating on processes and products.

Company Website: constructor.com

📝 Enhancement Note: Constructor appears to be a fast-paced, tech-forward company operating at the cutting edge of AI for e-commerce. The culture likely values technical expertise, data-driven decision-making, and a proactive approach to problem-solving and innovation. The remote-first nature necessitates strong self-management and communication skills.

📈 Career & Growth Analysis

Operations Career Level: This role is positioned as a Mid-Level Data Analyst, likely falling within the broader spectrum of Sales Operations or Revenue Operations support. It offers a direct impact on sales enablement and product feedback loops.

Reporting Structure: The role reports to a manager within the data or analytics function, but works very closely with Account Executives and Frontend Engineers, indicating a collaborative, project-based reporting dynamic.

Operations Impact:

• Sales Enablement: Directly contributes to improving the sales process by equipping AEs with better tools and insights for prospect engagement, thereby increasing demo effectiveness and conversion rates.
• Product Optimization: Provides critical user behavior insights that influence the development and refinement of core AI-powered search and recommendation systems, impacting the product's overall value proposition.
• Revenue Growth: By improving demo quality and supporting deal closures, this role has a tangible impact on driving revenue and customer acquisition for Constructor.

Growth Opportunities:

• Technical Skill Expansion: Deepen expertise in data analysis, BI tooling, Python for data science, and potentially gain exposure to large-scale data infrastructure and AI/ML model tuning.
• Domain Expertise: Develop specialized knowledge in e-commerce analytics, AI-driven discovery platforms, and sales operations strategies.
• Cross-Functional Leadership: Grow into roles that require more direct leadership of Sales Operations initiatives, product analytics projects, or managing cross-functional data initiatives.
• Career Path: Potential progression into Senior Data Analyst, Analytics Manager, Sales Operations Lead, or Product Analyst roles within Constructor.

📝 Enhancement Note: This role offers a strong foundation for a career in Operations, particularly for those interested in the intersection of data analytics, sales enablement, and product development within a high-growth tech company. The emphasis on direct impact on sales and product makes it an attractive opportunity for ambitious professionals.

🌐 Work Environment

Office Type: Fully Remote. There is no central physical office for day-to-day work. Office Location(s): While the role is based in Mexico, the team is fully remote across different locations, with a focus on supporting US-based sales teams.

Workspace Context:

• Asynchronous Communication: Expect a reliance on tools like Slack, email, and project management software for communication and collaboration, requiring clear and concise written updates.
• Collaborative Platforms: Utilize shared documents, version control systems (like Git), and virtual whiteboarding tools for team projects and knowledge sharing.
• Technology Stack: Access to modern development and collaboration tools is expected, including company-provided Apple laptops and potential home office stipends.
• Team Interaction: Opportunities for interaction will likely occur through scheduled virtual meetings, team-building games, and ad-hoc collaboration via messaging platforms.

Work Schedule:

• The core working hours are designed to overlap with the US Pacific Time zone (7 am - 3 pm PT). This ensures effective collaboration with the US-based sales team. Candidates need to be comfortable with this timezone commitment.

📝 Enhancement Note: Successful candidates will thrive in an autonomous, remote work environment that demands proactivity, strong self-discipline, and excellent virtual communication skills. The specific timezone requirement is a key factor for candidates to consider.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: Likely a brief call with HR or a recruiter to assess basic qualifications, cultural fit, and salary expectations.
• Technical Assessment: Expect a practical test or coding challenge focusing on SQL and Python for data analysis, potentially involving data manipulation, query writing, and visualization tasks.
• Hiring Manager Interview: A deeper dive into your experience, problem-solving approach, and understanding of the role's responsibilities, likely with the direct manager. This may include behavioral questions.
• Cross-Functional Interviews: Interviews with Account Executives and/or Frontend Engineers to assess collaboration skills, communication effectiveness, and ability to translate business needs into technical solutions.
• Portfolio Review: A dedicated session to walk through your prepared portfolio, discussing specific projects, methodologies, and the impact of your work.
• Final Round/Executive Interview: Potentially a final conversation with a senior leader to discuss strategic alignment and overall fit.

Portfolio Review Tips:

• Quantify Impact: For each project, clearly state the problem, your solution, the tools/techniques used, and most importantly, the measurable results (e.g., "Increased demo conversion rate by 15%," "Reduced data processing time by 30%").
• Showcase Process: Explain your thought process for analyzing data, building dashboards, or solving problems. Highlight your methodology for data cleaning, feature selection, and model tuning.
• Tailor to the Role: Select portfolio pieces that best demonstrate your ability to support sales teams, build analytical tools for non-technical users, and work with large datasets.
• Prepare a Narrative: For each portfolio item, have a concise story ready that explains the context, your contribution, and the outcome.
• Technical Depth: Be ready to discuss the technical details of your projects, including SQL query optimization, Python library usage, and BI tool functionalities.

Challenge Preparation:

• SQL & Python Proficiency: Practice writing efficient SQL queries and performing data manipulation and analysis using pandas. Be prepared for scenarios involving large datasets and complex joins.
• Dashboard Design: Understand principles of effective data visualization and dashboard design for business users. Be ready to discuss how you would structure a dashboard to meet specific AE needs.
• Problem Decomposition: Practice breaking down complex business problems into smaller, analytical components. Think about how you would approach identifying key metrics and data sources for a given scenario.
• Communication Skills: Prepare to articulate technical concepts clearly and concisely. Practice explaining your analytical approach and findings to both technical and non-technical audiences.

📝 Enhancement Note: The interview process is designed to rigorously assess both technical skills and the ability to apply them in a sales-enabling context. A well-prepared portfolio that highlights relevant projects and quantifiable achievements will be crucial for success.

🛠 Tools & Technology Stack

Primary Tools:

• SQL: Proficiency across various SQL dialects is essential for data extraction and manipulation.
• Python: Core for data analysis, scripting, and potentially model prototyping, utilizing libraries like pandas, NumPy, Matplotlib, Seaborn, and potentially scikit-learn.
• BI Tooling: Experience with platforms like Tableau, Looker, Power BI, or similar for creating interactive dashboards and reports for diverse audiences.

Analytics & Reporting:

• Data Visualization Libraries: Matplotlib, Seaborn, Plotly for creating insightful charts and graphs.
• Reporting Frameworks: Ability to structure and present findings effectively through reports and presentations.

CRM & Automation:

• CRM Systems (Understanding): While not explicitly stated as a requirement to manage, understanding how data flows from CRM systems (like Salesforce) into analytical workflows is beneficial.
• Data Warehousing/Lakes (Familiarity): Exposure to environments like AWS (S3, Redshift), Google Cloud Platform (BigQuery), or Snowflake would be advantageous given the "big data stack" mention.

📝 Enhancement Note: Candidates should be comfortable with a standard data science and BI technology stack. Familiarity with cloud data platforms and a conceptual understanding of CRM data flow will enhance their application.

👥 Team Culture & Values

Operations Values:

• Data-Driven Decision Making: A strong emphasis on using data to inform strategy, optimize processes, and measure impact.
• Customer Focus: Understanding that operations support ultimately aims to improve the customer experience and drive business success, particularly for prospects.
• Continuous Improvement & Curiosity: A mindset geared towards learning, experimenting, and constantly seeking ways to enhance efficiency and effectiveness.
• Collaboration & Empathy: Valuing teamwork, open communication, and supporting colleagues to achieve shared goals.
• Impact Orientation: Focusing on delivering tangible business value and measurable results.

Collaboration Style:

• Proactive & Cross-Functional: Actively engaging with sales, engineering, and product teams to understand needs and contribute solutions.
• Transparent Communication: Openly sharing insights, challenges, and progress through various communication channels.
• Feedback-Driven: Willingness to give and receive constructive feedback to improve individual performance and team processes.
• Problem-Solving Partnership: Working collaboratively to diagnose issues and co-create solutions.

📝 Enhancement Note: The company culture emphasizes technical excellence, a strong work ethic, and a collaborative spirit, all within a remote environment. Candidates who are proactive, data-oriented, and enjoy working in cross-functional teams will likely find this environment appealing.

⚡ Challenges & Growth Opportunities

Challenges:

• Timezone Alignment: Working effectively within the specified PT hours while based in Mexico requires strong time management and proactive communication.
• Balancing Sales Support & Product Insights: Juggling the immediate needs of Account Executives for demo tools with longer-term data exploration for product improvement.
• Rapidly Evolving AI Landscape: Staying current with advancements in AI and LLMs to effectively support and improve the company's core technology.
• Data Complexity at Scale: Managing and deriving insights from massive datasets requires robust analytical skills and efficient processing techniques.

Learning & Development Opportunities:

• AI/ML Specialization: Gain deeper insights into the application of AI and LLMs in e-commerce search and recommendations.
• Advanced Analytics Techniques: Develop expertise in predictive modeling, statistical analysis, and advanced BI implementations.
• Sales Operations Best Practices: Learn how data analytics directly drives sales effectiveness and revenue growth in a SaaS context.
• Cross-Functional Exposure: Broaden understanding of product development lifecycles and sales strategies through close collaboration.

📝 Enhancement Note: This role presents an excellent opportunity to grow in a dynamic tech environment, particularly for those interested in the intersection of data science, AI, and go-to-market strategies. The challenges are typical of high-growth tech companies and offer significant learning potential.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you built an analytical tool or dashboard to support a sales team. What were the key metrics, and what was the impact?"
• "How would you approach tuning an AI model for a specific e-commerce prospect based on their unique business needs?"
• "Walk me through your process for identifying opportunities to improve a recommendation system using user behavior data."
• "How do you ensure your data analysis and reporting are understood by non-technical stakeholders?"

Company & Culture Questions:

• "What interests you about Constructor's AI-driven approach to e-commerce search and discovery?"
• "How do you foster a sense of community and support within a fully remote team?"
• "Describe your experience working with Account Executives or sales teams. What are the key aspects of supporting them effectively?"
• "How do you stay curious and continuously improve your skills in the fast-paced field of data analysis?"

Portfolio Presentation Strategy:

• Structure: Begin with a brief overview of the project's objective, followed by your methodology, the tools used, key findings, and a clear articulation of the business impact (quantified wherever possible).
• Demonstrate Process: Be prepared to discuss the "why" behind your technical choices and how you navigated challenges.
• Highlight Collaboration: If applicable, explain how you collaborated with others on the project and how you communicated your findings.
• Focus on Relevance: Prioritize portfolio items that directly align with the responsibilities of this role, such as sales enablement tools, customer behavior analysis, or AI model performance evaluation.

📝 Enhancement Note: Interview preparation should focus on demonstrating both technical proficiency and the ability to apply analytical skills to drive sales outcomes and product improvements. Be ready to articulate your process and quantify the impact of your work.

📌 Application Steps

To apply for this operations position:

• Submit your application through the provided Workable link.
• Portfolio Customization: Select 2-3 key projects from your experience that best showcase your SQL, Python, BI dashboarding, and sales enablement skills. Prepare concise summaries and, if possible, visual aids for each.
• Resume Optimization: Tailor your resume to highlight experience in data analysis, BI tool usage, Python/SQL proficiency, and any contributions to sales processes or product insights within e-commerce or SaaS environments. Use keywords from the job description.
• Interview Preparation: Practice answering behavioral and technical questions, focusing on the STAR method (Situation, Task, Action, Result) for behavioral examples. Prepare to discuss your portfolio projects in detail.
• Company Research: Familiarize yourself with Constructor's platform, its target market (e-commerce), and its AI-driven approach. Understand the company's mission and values to articulate your alignment.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

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