PubMatic delivers superior revenue to publishers by being an SSP of choice for agencies and advertisers. PubMatic’s cloud infrastructure platform for digital advertising empowers app developers and publishers to increase monetization while enabling media buyers to drive return on investment by reaching and engaging their target audiences in brand-safe, premium environments across ad formats and devices. Since 2006, PubMatic has been expanding its owned and operated global infrastructure and continues to cultivate programmatic innovation. With a globally distributed workforce and no corporate headquarters, PubMatic operates 16 offices and eight data centers across North America, Europe, and Asia Pacific.
PubMatic is immediately hiring a strong Data Scientist or Machine Learning Engineer to join our growing team remotely.
Reporting to the Director of Machine Learning in Pacific Time, you will partner with Product and Engineering teams to solve problems with Machine Learning to identify trends and opportunities for the business. The ideal candidate will apply quantitative analysis, modelling, and data mining to help drive informed product decisions for PubMatic.
- Perform deep dive analysis to understand and optimize the key product KPIs
- Apply statistics, modelling, and machine learning to improve the efficiency of systems and relevance algorithms across our business application products
- Conduct data analysis to make product recommendations and design A/B experiments
- Partner with Product and Engineering teams to solve problems and identify trends and opportunities
- Collaborate with cross-functional stakeholders to understand their business needs, formulate and complete end-to-end analysis that includes data gathering, analysis, ongoing scaled deliverables and presentations
- BE/BTech or MTech degree with emphasis on coursework of a quantitative nature (e.g., Statistics, Computer Science, Engineering, Mathematics, Data Sciences)
- 2+ years of hands-on experience with design + implementation of Machine Learning models for solving business problems with statistical packages, such as R, MATLAB, Python (NumPy, Scikit-learn + Pandas) or MLlib
- Experience with articulating product questions and using statistics to arrive at an answer
- Experience with scripting in SQL - extracting large data sets and design of ETL flows
- Work experience in an inter-disciplinary/cross-functional field
- Deep interest and aptitude in data, metrics, analysis, trends and applied knowledge of measurement, statistics and program evaluation
- Distinctive problem-solving skills and impeccable business judgment
- Capable of translating analysis results into business recommendations