Senior Data Scientist / Machine Learning Engineer
- 305 Main St, Redwood City, CA 94063, USA
PubMatic is a publisher-focused sell-side platform for an open digital media future. We exist to help our clients succeed. We work tirelessly to optimize your performance while our SSP enables you to make smart, strategic decisions.
Featuring leading omni-channel revenue automation technology for publishers and enterprise-grade programmatic tools for media buyers, PubMatic's publisher-first approach enables advertisers to access premium inventory at scale.
Processing over one trillion ad impressions per month, PubMatic has created a global infrastructure to drive publisher monetization and control over their ad inventory.
Since 2006, PubMatic's focus on data and technology innovation has fueled the rise of the programmatic industry as a whole. Headquartered in Redwood City, California, PubMatic operates 13 offices and six data centers worldwide.
We are immediately hiring a strong Data Scientist or Machine Learning Engineer to join us in Redwood City - a proven 'doer' to develop, implement and extend data-intensive machine learning software for real-time auctioning, ad inventory estimation, and audience segmentations.
You will design and implement core components of our algorithms, as well as model and monetize the large amounts of data that PubMatic generates daily.
Working with our Data Science and AdServing teams, you will apply Machine Learning to help get things done.
- Development and implementation of data-intensive machine learning software for real-time auctioning, ad inventory estimation, audience segmentations, and other AdTech applications
- Working with data scientists, product managers, and software engineers to develop and support the software for new Machine Learning products
- Ensuring excellence in delivery to internal and external customers
- MS / PhD in STEM field
3+ years of hands-on industry work experience designing and building large-scale ML algorithms and ETL that are well-designed, cleanly coded, well-documented, operationally stable, and timely delivered
5+ years total analytical work, including academic research
Solid Experience with a mix of the following:
Python or R, including ML libraries (SKLearn, NumPy, caret, e1071), including CPU/GPU parallelization, matrix algebra, vectorization, linear programming, lambda programming, OOP
At least one of the DL frameworks (TensorFlow, PyTorch, Caffe, Theano, Keras, or alike)
- Graduate statistics and probability (inference, hypothesis testing, p-value, ANOVA, CLT, LLN, Bayes’ theorem, A/B testing, combinatorics, PDF/CDF, joint/conditional/marginal densities)
- Vector calculus (gradients, Jacobians, partial derivatives and integrals, optimization)
- Linear algebra (eigen values/vectors, inverses, decompositions, orthogonality, multi-linear)
- Time series (ARIMA, GARCH, forecasting, Kalman filter)
- Shallow ML algorithms: regressions, SVM, kMeans, kNN, NB, HMM, PCA, NMF, SVD, XGBoost, decision trees, ensemble methods (random forest)
- Deep NN algorithms: MLP, RNN, LSTM, CNN, GRU
- ML concepts: backprop, hyperparameter tuning (Bayesian optimization, grid/random search), regularization, learning rate, optimization
- Advanced work with SQL or NoSQL, including nested/join/aggregate queries, stored procedures, over partition by, basic stat functions
- Cloud compute engines (AWS, Azure, GCP and alike), ML on clusters of GPUs, SageMaker, Jupyter
- Excellent communication skills, cultural fit and natural curiosity in learning the ML developments and domain expertise
Nice to have:
- Experience in Programmatic advertising and RTB
- Deep reinforcement learning (Bellman equations, MDP, policy optimization, credit assignment, multi-agent, …)
- Proficiency with Spark (ML Lib, GraphX), Hadoop, Kafka, Hive
- Scala, Java, C/C++
- Record of STEM publications in top journals or conferences
- High rank at Kaggle competitions
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.
All your information will be kept confidential according to EEO guidelines.