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Chief Data Officer

As the Chief Data Officer at StellarTech you will champion a data-driven approach as the company's foundational strategy. Your responsibilities include creating and further development of data platform from the ground up, establishing both managerial and product analytics, developing market intelligence functions, and professional data management processes. Collaborating closely with the CTO, CPO, and other key business stakeholders, you will ensure that data insights and analytics support critical internal functions like Marketing, Monetization, Product, Payments, Finance, and Customer Support, driving informed decisions across the company.

We expect to find a mature and proactive visionary leader who not only understands the current landscape but also anticipates future trends in data science and analytics, a strategic thinker with a proven track record in building and managing analytics teams, who brought business outcomes.

Our company emerges from the innovative vision of the creator behind Welltech, a pioneer and one of the worldwide leaders in health and wellness technology with 200M Installs, aiming to integrate well-being into the digital landscape.

Building on the innovative groundwork laid by our founders, newly established StellarTech is poised to dive into the EdTech sector, crafting cutting-edge products and applications designed to revolutionize learning and educational experiences for millions of users. Our ambition doesn't stop there; we're also developing a suite of diverse tools aimed at enhancing productivity and engagement in various professional and personal contexts. Our mission is to harness the power of technology to create solutions that are not only innovative but also impactful, fostering growth and learning opportunities for people worldwide.

Data Platform Leadership: Take charge of the Data Platform’s ownership, and lead the platform development to support analytical functions across multiple mobile and web applications. Ensure the Data Platform is scalable, secure, and efficient, facilitating real-time data processing and analytics for various business units. Manage the integration of data sources and maintain data integrity, aligning the Data Model with business objectives.

Data Management Excellence: We are just starting our way, and, taking into account our ambitious goals, the Implementation of professional data management practices is critically important from the very beginning. It should include data governance, metadata management, quality control, and data protection, ensuring the organization's data assets are managed effectively and securely.

Business Intelligence and Reporting: Create and maintain operational reporting systems and dashboards for daily operations oversight, including app usage, marketing, and financial performance metrics. Implement advanced data visualization tools for accessible, real-time decision-making insights.

Strategic Insights and Decision Support: Provide executive leadership and stakeholders with strategic insights by analyzing data trends and market dynamics. Foster a culture of data-driven decision-making, especially in product development, marketing strategies, and customer experience. Develop business metrics, plans, and forecasts.

Data-Driven Culture: Foster a cross-functional collaborative environment. Сreation of self-service analytics to empower teams across Marketing, Monetization, Product, Payments, Finance, and Customer Support, facilitating a data-driven approach in their strategic planning and daily operations.

Leadership and Team Development: Assemble and lead the data team, defining objectives and key performance indicators that align with the company’s vision. Cultivate a culture of innovation, continuous improvement, and learning within the team.

Educational Background:

• A Master's degree in Computer Science, Data Science, or a closely related discipline. Distinction for contributions to the field, such as published research, participation in hackathons, and competitive accolades, will be viewed favorably.

Professional Experience:

• Minimum 5-7 years of experience in leading data analytics within a digitally-focused enterprise. Proven success in designing and executing a comprehensive data strategy.
• Successful track record in developing modern data processing architectures, alongside building scalable data platforms. Proficiency with Amazon Web Services (AWS) data stack components—like Redshift, S3, Glue, and Kinesis—is highly desirable.
• Expertise in data engineering practices, including the design and implementation of data architecture, ETL processes for efficient data transformation, data warehousing for centralized analysis, and automation of data pipelines.
• Strong expertise in analytical tools (Tableau, Power BI, SuperSet, etc.) and platforms (e.g., Google Analytics), data warehousing solutions, and SQL/NoSQL databases. Including self-service analytics solutions.
• Knowledge and experience of integrating with product analytical tools (Amplitude, Mixpanel) and marketing tooling (Meta, GoogleAds, BigSpy, etc.) Awareness of platform integration aspects. Strong practical experience in A/B tools. Practical experience of using 3rd party tools like Similarweb, Sensor Tower, etc.
• Proven ability to leverage data science and machine learning practices and technologies to drive tangible business improvements. Experience in the development and implementation of the full cycle of machine learning models. Specific experience in Large Language Models (LLMs) is an added advantage.
• Extensive experience in data management, encompassing governance policies, quality control mechanisms, data security protocols, metadata management, data integration, and lifecycle management. DAMA data management professional certification will be a plus.
• Expert knowledge of mobile and web application development, including key metrics and strategies for marketing performance, user acquisition, engagement, monetization, and retention - would be a plus.

Personal Attributes:

• Professional maturity, with a deep sense of responsibility and ownership.
• Commitment to transparency and honesty in all communications.
• Consistency, ability to deliver stable performance, and reliable outcomes steadily over time.
• Passion & Curiosity: A fervent enthusiasm for data, with a keen interest in discovering new insights and innovations.
• Team player, emphasizing collaboration, mutual support, and assistance.
• Embraces the "X-1000 mindset," aiming for monumental results with smart execution.
• Courageous, willing to take calculated risks.
• Autonomous and independent, capable of self-directed action.
• Hands-on management style, willing to engage directly with tasks when necessary.