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Machine Learning Engineer

5 Months ago • 1-3 Years • Data Analyst

Job Summary

Job Description

PubMatic seeks a Machine Learning Engineer to analyze data, optimize systems, and build models to improve product KPIs. You'll work with Product and Engineering teams to identify trends and drive informed decisions. Strong statistical analysis and machine learning skills in Python, R, or similar packages are essential.
Must have:
  • Machine Learning
  • Python/R/MATLAB
  • Data Analysis
  • Product Optimization
Good to have:
  • A/B Testing
  • SQL Scripting
  • ETL Flows
  • Cross-Functional
Perks:
  • Stock Options
  • Healthcare Insurance

Job Details

About the job

PubMatic (Nasdaq: PUBM) is an independent technology company maximizing customer value by delivering digital advertising’s supply chain of the future.

PubMatic’s sell-side platform empowers the world’s leading digital content creators across the open internet to control access to their inventory and increase monetization by enabling marketers to drive return on investment and reach addressable audiences across ad formats and devices.

Since 2006, our infrastructure-driven approach has allowed for the efficient processing and utilization of data in real time. By delivering scalable and flexible programmatic innovation, we improve outcomes for our customers while championing a vibrant and transparent digital advertising supply chain.

Job Description

We are immediately hiring a results-oriented Machine Learning Engineer to join our growing team in Pune .

Reporting to the Director of Machine Learning, you will partner with Product and Engineering teams to both solve problems and identify new opportunities for the business.

The ideal candidate will apply quantitative analysis, modeling, and data mining to help drive informed product decisions for PubMatic + get things done.

Responsibilities

  • Perform deep dive analysis to understand and optimize the key product KPIs
  • Apply statistics, modeling, 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

Qualifications

  • BE/BTech /MCA in Computers or equivalent
  • 1 to 3 years of hands-on experience designing Machine Learning models to solve 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

Return to Office: PubMatic employees throughout the global have returned to our offices via a hybrid work schedule (3 days “in office” and 2 days “working remotely”) that is intended to maximize collaboration, innovation, and productivity among teams and across functions.

Benefits: Our benefits package includes the best of what leading organizations provide, such as stock options, paternity/maternity leave, healthcare insurance, broadband reimbursement. As well, when we’re back in the office, we all benefit from a kitchen loaded with healthy snacks and drinks and catered lunches and much more!

Diversity and Inclusion: PubMatic is proud to be an equal opportunity employer; we don’t just value diversity, we promote and celebrate it. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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