Role

Triplelift, a fast-growing AdTech Supply Side Platform, tackling some of the most challenging problems in the world of digital advertising, is seeking an innovative, experienced, and hands-on Director of Data Science within our Data org to helm Data Science (DS) at Triplelift. As the Director of Data Science you will be at the forefront of driving innovation in the AdTech space. Leading our Data Science team, you will design and deliver advanced machine learning models and algorithms for real-time bidding, supply path optimization, and traffic shaping. This role involves managing an existing team of extremely talented data scientists, setting the vision and strategy for a world-class data science function and scaling the team as needed. Working with data at an unparalleled scale - think tens of millions of transactions per second and trillions of events daily - you will play a pivotal role in optimizing outcomes for publishers, demand-side platforms, and Triplelift alike. This is a unique opportunity to shape data science strategies and solutions at an unprecedented scale.

Responsibilities

• Define the vision and roadmap for data science initiatives, aligning with business goals
• Lead, mentor, and expand a team of talented data scientists, foster a collaborative, inclusive, and growth-oriented team culture, while identifying hiring needs and recruiting top talent to scale the team
• Drive exploratory research and experiments to analyze bidding behaviors in Triplelift’s real-time marketplace, and use it to develop, implement, and optimize state-of-the-art machine learning models for hyper low-latency, high-throughput, applications
• Innovate novel, cost-effective, solutions for real-time bidding systems, supply path optimization, and traffic shaping to maximize value for stakeholders
• Design scalable, efficient DS/ML systems capable of handling millions of inferences per second and processing petabytes of data daily, leveraging modern data science frameworks and cloud technologies to ensure robust and reliable systems
• Collaborate with engineering teams to deploy and maintain machine learning models in production environments, and help define and implement strategies for data modeling, infrastructure, and data warehousing for DS applications
• Monitor and evaluate the performance of deployed models, ensuring continual improvement and adaptation
• Define the technical vision and establish best practices for data science, collaborating with Product Management and Commercial stakeholders to brainstorm impactful applications, outline requirements, set priorities, and consistently deliver valuable solutions, while clearly communicating progress and outcomes
• Effectively communicate complex data science concepts to stakeholders with varying technical expertise
• Drive agile project management practices, ensure timely delivery of data science projects, and communicate project status, risks, and opportunities to senior leadership and stakeholders
• Stay up-to-date on emerging trends, tools, and technologies, and foster a culture of quality, innovation and continuous improvement, both within the Data Science team and the Data org as a whole
• Ensure the team adheres to high standards of data quality, governance, and security

Qualifications

• Master’s degree, or higher, in a related quantitative field (E.g. Mathematics, Computer Science, Engineering, Economics, or Operations Research), with a strong foundation in statistics, machine learning, and advanced analytics techniques
• 8+ years of relevant experience in Data Science, with at least 5+ years in a leadership role, strong experience in mentoring and managing engineering teams in a fast-paced environment, and demonstrated ability to hire top talent to scale teams effectively.
• Deep understanding of real-time systems, predictive modeling, and algorithm development, and proven expertise in building and scaling machine learning systems for high-throughput, low-latency environments, preferably in AdTech
• Demonstrated ability to lead and inspire geographically distributed teams, fostering career growth and team morale
• Proficiency with data science tools and programming languages, such as Python, TensorFlow, PyTorch, or similar, and experience with cloud-based platforms (E.g. AWS or GCP) and big data tools (E.g. Databricks, Snowflake, Grafana, Looker, MySQL)
• Deep knowledge of ML tools and libraries (E.g. scikit-learn, pandas, ONNX, PyTorch) to quickly analyze data and prototype models that can be used in high volume distributed systems
• Demonstrated ability to lead and inspire teams while fostering career growth and development
• Excellent communication and stakeholder management skills, with experience working cross-functionally with diverse teams (E.g. Engineering, Product and Commercial teams)
• Strong project management skills with expertise in Agile methodologies and tools like JIRA
• Exceptional analytical and problem-solving skills, with a focus on delivering business impact

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