Data Scientist
Data Scientist / Algorithm Engineer role focused on building advanced machine learning models and algorithms to optimize CPA advertising campaigns, driving conversion volume while staying within budget constraints in the AdTech space.
Join MGID as a Data Scientist and become part of a team shaping the future of AdTech!
We are a forward-thinking team striving to develop and implement cutting-edge algorithms for optimizing advertising campaigns in AdTech. Currently, our primary goal is to enable CPA (Cost Per Action) campaigns to achieve the following objectives:
Hit CPA targets by ensuring conversions occur at a specified cost.
Scale conversions volume while maintaining alignment with the CPA target.
Maximize conversions within the client’s budget.
This role offers the unique opportunity to contribute directly to the development of these solutions, driving innovation in the AdTech space and shaping the future of campaign optimization.
We are looking for a self-driven, proactive, and results-oriented professional who is not afraid to take ownership: analyze data, identify bottlenecks, and come up with practical solutions quickly.
Requirements
What You Will Do:
Data Analysis: explore large-scale event data to identify trends, patterns, and anomalies, generate insights/ideas, evaluate campaigns’ performance, and support decision-making based on findings.
Algorithm Development: design, implement, optimize and test algorithms for CPA optimization.
Modeling and Optimization : build and refine predictive models to improve decisions for CPA campaigns, ensuring alignment with business objectives.
Stakeholder Collaboration: work closely with product/business/tech teams to turn technical findings into actionable decisions.
Experimentation and Validation : conduct and evaluate A/B tests to assess the impact of algorithm changes.
Visualization and Reporting : create dashboards and visualizations to track key performance indicators (KPIs) and communicate findings to stakeholders.
Who You Are:
Thinks proactively: Identifies data anomalies, forms and tests hypotheses, and designs practical, end-to-end solutions.
Dives deep into data: Analyzes complex datasets to extract valuable insights, with a proven ability to visualize and communicate findings clearly.
Owns outcomes, not just tasks: Drives communication through insights, bringing structured conclusions, hypotheses, and recommendations to the team.
Enjoys complex, ambiguous problems where the right answer is not obvious from the start.
Has at least 4 years of proven, hands-on experience in data science, with a strong understanding of optimization problems.
Proficient in Python and SQL, including data manipulation and feature engineering.
Has expertise in machine learning techniques and tools (e.g., CatBoost, XGBoost, TensorFlow, PyTorch, scikit-learn).
Has experience with big data technologies (Spark, Hadoop) and processing large datasets.
English: Intermediate/Upper-Intermediate. Ukrainian: Fluent
Will be a plus:
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Posted June 20, 2026