Data Scientist

Our Customer:
Our customer is a technology company developing data-driven solutions for digital advertising and real-time campaign optimization. The team works with large-scale data and Machine Learning to support automated advertising decisions and improve campaign performance.

Your tasks:

• Develop, improve, and operate ML models used in production advertising systems.
• Work on ML problems related to bidding, bid optimization, and real-time advertising decision-making.
• Develop models for CTR/CVR prediction.
• Optimize campaign performance, budget allocation, and pacing.
• Work on ranking and decisioning models for advertising systems.
• Analyze large-scale advertising data and identify opportunities for optimization.
• Translate business and advertising problems into practical Data Science / ML solutions.
• Evaluate model performance and business impact using relevant advertising KPIs.
• Conduct experiments and A/B testing to validate and improve ML solutions.
• Collaborate with engineering and product teams to deploy and continuously improve production models.

Required experience and skills:

• 5+ years of commercial experience in Data Science / Applied Machine Learning.
• 3+ years of hands-on experience in AdTech / Programmatic Advertising.
• 2+ years of direct experience with RTB / real-time bidding systems.
• Commercial experience applying ML/Data Science to advertising optimization.
• Hands-on experience with bidding or bid optimization.
• Experience with CTR/CVR prediction, campaign optimization, ranking, pacing, budget allocation, or advertising decisioning.
• Experience developing, improving, or operating ML models in production.
• Strong Python skills.
• Strong SQL skills and experience working with large-scale datasets.
• Experience translating business problems into ML/Data Science solutions.
• Strong analytical and problem-solving skills.
• Strong English communication skills.

Would be a plus:

• Experience with DSP platforms.
• Experience with bidder logic, bidding algorithms, or bid-price optimization.
• Knowledge of OpenRTB and auction dynamics.
• Experience with real-time decisioning or pre-bid optimization/filtering.
• Experience with user acquisition, retargeting, or performance advertising.
• Experience with large-scale real-time ML.
• Experience with online experimentation / A/B testing.
• Experience with contextual bandits, online learning, or reinforcement learning.

Working Conditions:

• 5-day working week, 8-hour working day.
• Remote work.

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