Product Designer, Analytics (Remote - India)

📍 Job Overview

Job Title: Product Designer, Analytics
Company: Jobgether (Partner Company)
Location: India
Job Type: Full-Time
Category: Product Design / Data Analytics Operations
Date Posted: 2025-10-27
Experience Level: Mid-Level (3+ years)
Remote Status: Fully Remote

🚀 Role Summary

• Design and deliver intuitive, actionable analytics experiences that empower users with data-driven insights.
• Translate complex datasets into clear, visually compelling data visualizations and dashboards.
• Collaborate cross-functionally with Product Management and Engineering to define and execute analytics roadmaps.
• Champion user needs through research and advocate for data accessibility for non-technical users.
• Contribute to a culture of design excellence, continuous improvement, and knowledge sharing within the design team.

📝 Enhancement Note: This role, while titled Product Designer, has a strong emphasis on analytics and data visualization, suggesting a focus on the operational aspects of making data understandable and actionable for business users. This aligns with GTM operations and revenue operations roles that rely on data interpretation for strategic decision-making.

📈 Primary Responsibilities

• Design end-to-end analytics user experiences, encompassing dashboards, reports, predictive insights, and recommendation systems.
• Develop user-centric data visualizations that transform complex datasets into clear, actionable insights, accessible to both technical and non-technical stakeholders.
• Partner closely with Product Managers and Engineers to define analytics product roadmaps, prioritize features, and ensure seamless implementation of design solutions.
• Create and maintain a reusable library of data visualization patterns and design system components to ensure consistency and efficiency across analytics products.
• Conduct user research and stakeholder interviews to deeply understand how data informs business decisions and identify opportunities for enhanced analytics capabilities.
• Define key performance indicators (KPIs) for analytics features and utilize analytics, A/B testing, and feedback tools to measure and validate design impact.
• Actively contribute to the design team's culture through participation in design critiques, mentorship of junior designers, and knowledge sharing sessions.

📝 Enhancement Note: The responsibilities highlight a blend of core UX/UI design principles with a specific focus on data interpretation and translation, crucial for operational efficiency and data-driven decision-making. The emphasis on "actionable insights" and "data-driven decisions" directly ties into the core objectives of revenue and sales operations.

🎓 Skills & Qualifications

Education: Bachelor's degree in Design, Human-Computer Interaction, Computer Science, or a related field, or equivalent practical experience.

Experience: Minimum of 3 years of experience in Product Design, UX Design, or a similar role, with a proven track record of designing data-heavy interfaces and analytics dashboards.

Required Skills:

• User Experience (UX) Design: Deep understanding of UX principles, user-centered design methodologies, and the ability to translate user needs into intuitive product flows.
• Visual Design for Data: Strong visual design skills with a focus on creating effective and aesthetically pleasing data visualizations, charts, and dashboards.
• Figma Proficiency: Expert-level proficiency in Figma for design, prototyping, and collaboration.
• Prototyping & User Research: Experience with creating interactive prototypes and conducting user research, usability testing, and stakeholder interviews.
• Analytics Concepts: Solid understanding of fundamental analytics concepts, including descriptive statistics, data interpretation, and the ability to make complex data accessible to non-technical users.
• Collaboration & Communication: Excellent cross-functional collaboration and communication skills, with the ability to articulate design decisions and rationale clearly to diverse teams.
• Design System Contribution: Experience in developing or contributing to design systems and reusable component libraries.

Preferred Skills:

• Analytics & Research Platforms: Familiarity with analytics and user research platforms such as Pendo, Sigma, or Maze.
• Small Business Focus: Prior experience designing for small business owners or individuals who rely heavily on data for decision-making.
• Predictive Analytics/AI: Interest or experience in designing for predictive analytics, AI-driven insights, or recommendation systems.
• Data Storytelling: Ability to craft compelling narratives around data and insights.

📝 Enhancement Note: The required skills emphasize a strong foundation in design tools and methodologies, but the "Analytics Concepts" and "Preferred Skills" in predictive analytics and AI are critical differentiators for this role, pointing towards a need for a designer who can operationalize advanced data capabilities.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Showcase end-to-end design process for at least 2-3 complex analytics or data visualization projects.
• Clearly articulate the problem statement, user research insights, design challenges, and your specific contributions.
• Demonstrate the application of UX and UI design principles to make complex data understandable and actionable.
• Include examples of data visualizations, dashboards, and reporting interfaces you have designed.
• Highlight how your designs empowered users to make data-driven decisions and achieved measurable business outcomes.

Process Documentation:

• For each project, detail the user research methodologies employed, including how user needs were identified and translated into design requirements.
• Explain the iterative design and prototyping process, including how feedback was incorporated to refine the solution.
• Illustrate the collaboration process with product managers and engineers, showing how you worked together to define scope and implement designs.
• Present the metrics and analytics used to validate the success of your designs, demonstrating ROI and impact on user behavior or business objectives.

📝 Enhancement Note: A strong portfolio is paramount for this role, requiring candidates to not only display design aesthetics but also a robust understanding of how their designs facilitate data analysis and operational efficiency. The emphasis on "measurable business outcomes" and "ROI" is key for operations-focused roles.

💵 Compensation & Benefits

Salary Range: As this is a remote position based in India, and specific salary details are not provided, a competitive salary range would typically fall between ₹1,000,000 to ₹2,500,000 per annum for a Product Designer with 3+ years of experience in the tech industry. This estimation is based on market research for similar mid-level Product Designer roles in India, considering the demand for data analytics expertise and the fully remote work arrangement.

Benefits:

• Competitive Salary: A competitive compensation package designed to attract and retain top talent.
• Growth Opportunities: Access to professional development programs and mentorship opportunities to foster career advancement.
• Fully Remote: A 100% remote work arrangement, offering flexibility and work-life balance.
• Paid Time Off: Generous paid time off to ensure well-being and work-life integration.
• Wellness Initiatives: Programs and resources dedicated to supporting employee health and well-being.
• Inclusive Culture: A collaborative and dynamic design culture that values diversity and inclusion.
• Impactful Work: The opportunity to work on cutting-edge predictive analytics and AI-driven insights that influence business outcomes.

Working Hours: The role is full-time, typically requiring approximately 40 hours per week. While fully remote, candidates are expected to align with core business hours for effective collaboration with cross-functional teams, likely within Indian Standard Time (IST) or a closely related timezone. Flexibility may be available, particularly for asynchronous work, but consistent availability during key collaboration periods is expected.

📝 Enhancement Note: The salary range is an estimate based on typical Indian tech market compensation for mid-level designers. The benefits are directly extracted from the job description, with an emphasis on aspects attractive to operations professionals seeking growth and flexibility.

🎯 Team & Company Context

🏢 Company Culture

Industry: Technology / Talent Matching Platform (Jobgether) and Partner Companies in various tech sectors. Company Size: Jobgether, as a platform, likely operates with a lean, agile team, while its partner companies can vary significantly in size. This role is for a partner company, so the specific team size and structure will depend on that entity. Founded: Jobgether was founded to leverage AI for talent matching, indicating a forward-thinking, tech-centric approach to recruitment and employment. The partner company's founding date and history would be specific to them.

Team Structure:

• Operations Focus: The role is within a product design team that directly supports analytics capabilities, implying close collaboration with product managers, data scientists, and engineers.
• Reporting: Likely reports to a Design Lead, Head of Product, or a similar managerial role within the partner company's product organization.
• Cross-functional Collaboration: High degree of interaction with Product Management (for understanding business needs and strategy) and Engineering (for implementation and technical feasibility).

Methodology:

• Data-Driven Design: The core of this role is to operationalize data through design, emphasizing data analysis, user insights, and measurable outcomes.
• Agile Development: Expect to work within agile frameworks, participating in sprints, stand-ups, and iterative development cycles.
• User Advocacy: A strong emphasis on understanding and advocating for the end-user, especially in translating complex data into accessible formats.

Company Website: https://jobgether.com/ (for Jobgether platform details) - Specific partner company website is not provided.

📝 Enhancement Note: Understanding Jobgether's AI-driven approach provides insight into the technological sophistication and data-centricity expected. This role's focus on analytics design is crucial for any company aiming to improve its operational intelligence and decision-making.

📈 Career & Growth Analysis

Operations Career Level: This is a Mid-Level Product Designer role, focused on a specialized area (Analytics) that bridges design and operational data insights. It requires a solid foundation in design principles combined with an understanding of how data impacts business operations.

Reporting Structure: The designer will likely report to a Design Manager or Head of Product within the partner company. They will work closely with Product Managers and Engineers, forming a core product development pod.

Operations Impact: The designer's work directly impacts the partner company's ability to leverage data for strategic decision-making. By creating intuitive analytics experiences, this role empowers business stakeholders (potentially including sales, marketing, and operations teams) to understand performance, identify trends, and make informed operational adjustments, thereby driving business growth and efficiency.

Growth Opportunities:

• Specialization: Deepen expertise in data visualization, analytics design, and potentially AI/ML-driven insights.
• Leadership: Progress to a Senior Product Designer role, potentially leading design initiatives for analytics products or mentoring junior designers.
• Cross-functional Skill Development: Gain deeper insights into business operations, product strategy, and engineering workflows through close collaboration.
• Industry Exposure: Work with various data sets and business challenges relevant to the partner company's industry.

📝 Enhancement Note: This role offers a unique path for designers interested in the operational side of data, providing a stepping stone to more strategic product roles or even transitioning into product management with a strong analytical focus.

🌐 Work Environment

Office Type: Fully Remote. This implies a distributed team environment where collaboration relies heavily on digital tools and asynchronous communication.

Office Location(s): India. While remote, the role is designated for candidates residing within India, likely to align with local employment laws, payroll, and potentially some timezone overlap for core team interactions.

Workspace Context:

• Digital Collaboration: Expect to use a suite of collaboration tools (e.g., Slack, Zoom, Miro, Figma) for communication, ideation, and design reviews.
• Tooling: Access to design software (Figma), prototyping tools, user research platforms, and potentially analytics tools will be provided or expected.
• Team Interaction: Regular virtual team meetings, design critiques, and cross-functional sync-ups will be the norm. The success of this environment depends on proactive communication and a culture of trust.

Work Schedule: Full-time (approx. 40 hours/week), with flexibility inherent in a remote setup. However, availability during core business hours for critical team interactions and meetings will be necessary.

📝 Enhancement Note: The fully remote nature necessitates strong self-discipline, proactive communication, and proficiency with digital collaboration tools. This aligns with the operational requirement for efficiency and adaptability in a distributed workforce.

📄 Application & Portfolio Review Process

Interview Process:

1. Application Screening: Initial review of CV and LinkedIn profile by Jobgether's AI, followed by a potential manual review, to assess core qualifications against job requirements.
2. Hiring Manager/Recruiter Screen: A brief introductory call to discuss your background, interest in the role, and basic fit.
3. Portfolio Presentation & Design Challenge: A key stage involving presenting your portfolio, highlighting relevant analytics design projects, and potentially completing a design challenge (e.g., designing a dashboard for a specific use case, critiquing an existing data visualization).
4. Team/Cross-functional Interviews: Interviews with Product Managers, Engineers, and potentially other designers to assess collaboration style, technical understanding, and cultural fit.
5. Final Interview: Potentially with a senior leader (e.g., Head of Product, VP of Design) for final evaluation.

Portfolio Review Tips:

• Curate Strategically: Select 2-3 projects that best showcase your experience in designing analytics dashboards, data visualizations, and user-centric data experiences. Prioritize projects where you can demonstrate a clear impact on operational decision-making.
• Tell a Story: For each project, clearly articulate the problem, your role, the design process, key decisions, and the measurable outcomes. Emphasize how your design solutions solved a specific business or user problem related to data.
• Showcase Process: Detail your approach to user research, data interpretation, UX flows, and visual design. Explain why you made certain design choices, especially concerning data representation and user comprehension.
• Highlight Analytics Context: Explicitly mention your understanding of analytics concepts and how you translated complex data into actionable insights. If you have experience with predictive analytics or AI-driven features, make sure to highlight that.
• Quantify Impact: Whenever possible, use metrics to demonstrate the success of your designs (e.g., increased user engagement with dashboards, improved data accuracy, faster decision-making times).

Challenge Preparation:

• Understand the User: If given a design challenge, focus on understanding the target user and their specific data needs. Who are they? What decisions do they need to make? What data is critical for them?
• Data Prioritization: Practice identifying and prioritizing key data points for a given scenario.
• Visualization Selection: Be prepared to justify your choice of charts and visualizations based on the data type and the insights you want to convey.
• Design System Thinking: Consider how your design would fit into an existing design system or how reusable components could be applied.
• Communication is Key: Clearly articulate your thought process, design decisions, and any assumptions you are making throughout the challenge.

📝 Enhancement Note: The emphasis on a portfolio review and potential design challenge underscores the practical, output-oriented nature of this role, which is common for operations-focused positions where demonstrating tangible results is crucial.

🛠 Tools & Technology Stack

Primary Tools:

• Design & Prototyping: Figma (required). Proficiency is essential for design, collaboration, and prototyping.
• User Research & Analytics Platforms: Pendo, Sigma, Maze (familiarity preferred). These tools are key for understanding user behavior within products and gathering feedback.
• Collaboration Tools: Slack, Zoom, Miro, Asana/Jira (expected). Essential for remote team communication, ideation, and project management.

Analytics & Reporting:

• Data Visualization Libraries/Tools: While not explicitly stated, familiarity with how data is rendered (e.g., D3.js concepts, Tableau, Power BI) can be beneficial for understanding technical constraints and possibilities.
• Internal Analytics Dashboards: The candidate will be designing for these systems, so understanding their purpose and user needs is critical.

CRM & Automation:

• Not directly specified for the designer role, but understanding how product analytics data might feed into or be influenced by CRM systems (like Salesforce) or marketing automation platforms could be a plus for understanding the broader business context.

📝 Enhancement Note: Proficiency in Figma is non-negotiable. Experience with analytics and user research platforms directly supports the operational goal of creating data-informed designs and measuring their effectiveness.

👥 Team Culture & Values

Operations Values:

• Data-Driven Decision Making: A core value, reflected in the role's focus on designing analytics experiences that empower users with data.
• User-Centricity: Deep understanding and advocacy for the end-user are paramount, especially in making complex data accessible and useful.
• Collaboration & Transparency: Essential for a remote team, fostering open communication and shared understanding across functions.
• Continuous Improvement: A commitment to iterating on designs based on feedback, data, and evolving user needs.
• Efficiency & Impact: Designing solutions that not only look good but also drive tangible business results and operational improvements.

Collaboration Style:

• Cross-functional Integration: Expect to work closely with Product Managers to define strategy and requirements, and with Engineers to ensure feasibility and successful implementation.
• Iterative Feedback Loops: Regular design critiques, usability testing sessions, and stakeholder reviews are likely part of the process.
• Knowledge Sharing: A culture that encourages sharing best practices, learnings, and design patterns to elevate the entire team's capabilities.

📝 Enhancement Note: The values emphasize a pragmatic, results-oriented approach to design that aligns with operational excellence. The collaborative style points to a need for strong interpersonal and communication skills, crucial for effective GTM and RevOps alignment.

⚡ Challenges & Growth Opportunities

Challenges:

• Translating Complexity: The primary challenge will be translating intricate datasets and advanced analytics concepts into simple, intuitive user experiences for a potentially diverse user base.
• Balancing User Needs and Technical Constraints: Designing effective analytics tools requires navigating the trade-offs between ideal user experiences and the technical limitations of data platforms and development resources.
• Measuring Design Impact: Quantifying the direct impact of design decisions on business outcomes and operational efficiency can be challenging but is a critical aspect of this role.
• Staying Ahead of Data Trends: The field of data analytics, AI, and machine learning is constantly evolving; staying current with new technologies and design patterns will be an ongoing challenge.

Learning & Development Opportunities:

• Advanced Analytics Design: Deepen expertise in designing for predictive analytics, AI-driven insights, and complex data storytelling.
• Product Strategy: Gain a deeper understanding of product strategy and how analytics design contributes to overall business goals.
• Cross-Functional Acumen: Develop a strong understanding of sales, marketing, and operational processes through close collaboration.
• Mentorship: Benefit from mentorship opportunities within the design team and potentially from product or engineering leaders.
• Industry Exposure: Gain experience across different data challenges and user needs relevant to the partner company's sector.

📝 Enhancement Note: These challenges and opportunities are framed to resonate with operations professionals, highlighting the strategic importance of design in driving business performance and the potential for skill development in a rapidly evolving tech landscape.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you had to design an analytics dashboard for a non-technical audience. What were the key challenges, and how did you ensure the data was actionable?" (Focus on user empathy, simplification, and impact.)
• "How do you approach the design of predictive analytics features? What are the unique UX considerations compared to descriptive analytics?" (Highlight understanding of AI/ML UX, trust-building, and ethical considerations.)
• "Walk us through a project where your design decisions directly influenced a business outcome or operational improvement. What metrics did you use to measure success?" (Emphasize data storytelling, ROI, and quantifiable results.)

Company & Culture Questions:

• "What interests you about designing analytics experiences for businesses, particularly in the context of data-driven decision-making?" (Connect your passion to operational efficiency and business growth.)
• "How do you contribute to a collaborative design culture, especially in a remote environment?" (Showcase proactive communication, feedback skills, and team spirit.)
• "How do you stay updated on the latest trends in data visualization, UX design, and AI?" (Demonstrate continuous learning and industry awareness.)

Portfolio Presentation Strategy:

• Focus on Relevance: Select projects that most closely align with designing analytics interfaces, dashboards, and data-driven experiences.
• Detail Your Process: Clearly articulate your problem-solving approach, research methods, design iterations, and rationale behind key decisions, especially concerning data representation.
• Quantify Impact: Be ready to discuss the business impact of your designs using metrics. If direct metrics aren't available, discuss how you would measure success and what KPIs are relevant.
• Demonstrate Collaboration: Explain how you worked with product managers and engineers. Highlight instances where your design input shaped the product roadmap or technical implementation.
• Prepare for a Challenge: Be ready to tackle a hypothetical design challenge related to data visualization or analytics, demonstrating your problem-solving skills and design thinking on the spot.

📝 Enhancement Note: Preparing for these types of questions and presentation strategies will equip candidates to demonstrate their understanding of data's operational role and their ability to design solutions that drive business value.

📌 Application Steps

To apply for this Product Designer, Analytics position:

• Submit your application through the provided link on Workable.
• Portfolio Customization: Tailor your portfolio to prominently feature 2-3 analytics design projects. Clearly articulate the business problem, your design process, your specific contributions, and the measurable impact on data-driven decision-making or operational efficiency.
• Resume Optimization: Ensure your resume highlights keywords such as "Product Design," "Analytics," "Data Visualization," "UX," "Figma," "User Research," and any experience with "Predictive Analytics" or "AI-driven insights." Quantify achievements wherever possible.
• Interview Preparation: Practice presenting your portfolio with a clear narrative, focusing on how your designs solve operational challenges. Prepare to discuss your design process and rationale for specific data visualization choices.
• Company Research: Research Jobgether's platform and understand their AI-driven approach to talent matching. While this role is with a partner company, understanding the parent platform's ethos provides context for a data-centric tech environment.

⚠️ 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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