Middle/Senior Business Intelligence Analyst

MGID is a global native advertising platform that helps brands reach unique local audiences at scale. At MGID, we empower brands and publishers to collaborate transparently through our privacy-first targeting technology. This enables advertisers to drive performance and awareness while allowing publishers to retain and monetize their audiences. Today, we’re creating innovative technologies, and with your help, we aim to reach even greater heights.

We are looking for a Business Intelligence Analyst who is passionate about turning complex commercial data into clear business decisions and measurable growth. You will play a key role at the intersection of Business Intelligence and commercial strategy, partnering closely with Sales, Finance, and senior leadership to shape how we measure performance, identify growth opportunities, and drive strategic initiatives. We are looking for a proactive, business-minded professional who enjoys challenging assumptions, uncovering actionable insights, and transforming data into recommendations that influence business outcomes. If you thrive in a fast-paced, data-driven environment and enjoy building scalable analytics frameworks that support smarter decision-making, we'd love to meet you.

Requirements

Who You Are:

• Bachelor's or Master's degree in Business Analytics, Engineering or a related field

• Minimum of 5 years of relevant professional experience in business analysis, commercial analytics, or a similar role.

• Prior experience working with commercial or sales teams in medium to large organizations is highly preferred.

• Strong hands-on experience with SQL and BI tools such as Tableau or Power BI, including dashboard development and translating business needs into effective visual reporting.

• Industry experience in fintech, e-commerce, digital marketing, or digital technology is strongly preferred.

• Demonstrated ability to work with commercial data, generate insights, and support strategic decision-making.

What You’ll Do:

• Support the Commercial team with data-driven decision-making by delivering actionable insights and performance analysis.

• Review, optimize, and drive client acquisition and rewards programs across both supply and demand sides of the business.

• Analyze product usage, customer behavior, acquisition funnels, and client lifecycle data to identify opportunities for growth, retention, and monetization.

• Partner with Product, Data, Sales, and Finance teams to evaluate how product initiatives and new features influence commercial performance.

• Conduct cohort, segmentation, funnel, and performance analysis to uncover business drivers and support product and commercial decisions.

• Introduce and standardize methodologies for client referral programs to ensure consistency and measurable impact.

• Analyze the customer acquisition journey and implement a unified client lifecycle framework and common business definitions across the organization.

• Support the development, review, and company-wide rollout of key performance indicators.

• Provide sales projections and commercial performance analysis across global markets.

• Prepare quarterly sales forecasts as part of the regular business planning cycle.

• Define and implement the necessary metrics to evaluate commercial performance and monitor strategic initiatives.

• Forecast, assess, and track the performance of new projects and individual campaigns led by commercial teams.

Languages proficiency:

• Ukrainian - Fluent (nice to have)

• English - Advanced

At MGID, we thrive on innovation, collaboration, and a passion for AdTech. Our culture is built on openness, transparency, and a shared drive for excellence. We empower our teams to take bold steps, embrace challenges, and grow together in a dynamic, people-first environment. Here, your ideas matter, your contributions are valued, and your potential has no limits. Join us and shape the futureof digital advertising!

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Highlights

Drive smarter commercial decisions through data-driven insights, forecasting, and performance analytics.

Originally posted on Himalayas