BidMachine is a high-performance RTB exchange built on a modern technology stack. Every day we process petabytes of data, and serve billions of ad requests for tens of millions of mobile application users around the world. We are looking for a Data Team Lead to make the team even stronger.

Requirements

• Experience: 5+ years of experience in data engineering, data science, or analytics roles, with at least 2 years in a leadership or management capacity.
• Technical Expertise:
  • Strong understanding of SQL, Python, and data modeling.
  • Experience with big data technologies (e.g., Hadoop, Spark, Redshift, BigQuery).
  • Familiarity with cloud-based data platforms (e.g., AWS, GCP, Azure).
  • Expertise in machine learning and predictive modeling, with knowledge of common frameworks (e.g., TensorFlow, PyTorch).
• AdTech Experience: Knowledge of the digital advertising ecosystem, programmatic advertising, and common metrics like CPM, CTR, and ROI is highly preferred.
• Leadership Skills: Proven ability to manage, mentor, and grow a high-performing data team.
• Problem-Solving: Strong analytical mindset with a proven track record of solving complex business problems through data.
• Collaboration: Excellent communication skills, with the ability to work cross-functionally and influence decision-making.
• Education: Bachelor’s or Master’s degree in a relevant field (e.g., Computer Science, Data Science, Statistics).

Nice to have

• Experience with Databricks platform;
• Experience with Druid (or any other OLAP);
• Experience with Rust;
• Basic ML and data analytics;
• Basic Scala and functional programming knowledge.

Responsibilities

• Team Leadership: Lead, mentor, and manage a team of data engineers, data scientists, and analysts to ensure successful project delivery and team development.
• Data Strategy: Collaborate with stakeholders to define and execute the company’s data strategy, aligning with business goals.
• Data Infrastructure: Oversee the design and maintenance of scalable data infrastructure and pipelines to support real-time and batch data processing.
• Machine Learning & AI: Drive the adoption of machine learning algorithms and predictive analytics to optimize ad performance and monetization strategies.
• Reporting & Analytics: Lead the creation of advanced analytics and reporting tools to provide actionable insights into user behavior, campaign performance, and ad revenue optimization.
• Collaboration: Work closely with the Product, Engineering, and Business teams to ensure that data initiatives align with product development and business objectives.
• Data Governance: Establish best practices for data integrity, privacy, and compliance, ensuring data accuracy and regulatory adherence.
• Innovation: Stay ahead of industry trends in AdTech and data technology, identifying new opportunities for leveraging data to improve customer outcomes and business results.