Principal Data Scientist
Are you passionate about using cutting edge data science techniques to help protect the world against cyberthreats? Join us and you’ll work with unrivaled data sets to help protect large businesses in the world’s digital transactions and the lifestyles they enable. What makes this problem so challenging is the dynamic nature of the threat landscape.
You will bring a strong knowledge of using a variety of data mining and data analysis methods to build and implement models, algorithms, and simulations. Your expertise and passion will keep us ahead of the newest cyberthreats. You will mine, interpret, and clean our data; and we will rely on you to stay curious, ask questions, connect the dots, and uncover opportunities that lie hidden. You will be part of the design and development of new groundbreaking solutions that will guide the next generation of security solutions.
- Help us build our next generation machine learning solutions
- Innovate new ways to use existing technologies, incorporate novel open source technologies, and come up with their own solutions to our machine learning problems
- Use analytical rigor and statistical methods, programming, data modeling, simulation, and advanced mathematics to analyze large amounts of data, recognizing patterns, finding opportunities, posing business questions, and making valuable discoveries
- Understand and analyze data sources including sampling biases, accuracy, and coverage
- Break apart problems scientifically, providing insight into your recommendations and findings to both technical and non-technical partners
- Research new ways for modeling and predictive behavior for large scale projects
- Generate and test hypotheses, designing experiments to answer targeted questions of advanced complexity
- Collaborate with data engineers to identify data preparation, cleansing, and ETL pipelines
- Document projects including business objective, data gathering and processes, leading approaches, final algorithm, and a detailed set of results and analytical metrics
- Validate score performance
- Advanced degree in Machine Learning, Computer Science, Electrical Engineering, Physics, Statistics, Applied Math, or other quantitative fields
- 4 years of industry experience in machine learning
- 3 years of working experience in analytics, data mining, and/or predictive modeling, and data interpretation
- Experience with distributed systems like Hadoop or Spark a plus
- Strong working knowledge of machine learning algorithms that may include Naïve Bayes, Decision Trees, SVM, Logistic Regression, Classification, and Boosting
- Significant Deep Learning experience
- Proven track record in modifying and applying advanced algorithms to address practical problems
- Confident interacting with business peers to understand and identify the use case, with a strong ability to articulate solutions and present them to business partners
- Strong coding skills in one of the following: Python, R, or PySpark
- Experience with Hadoop and NoSQL or related technologies
- Knowledge of NLP/Text mining techniques and related open source tools
To stay ahead of the curve, it’s critical to know where the curve is, and how to anticipate the changes we may be facing. For the fastest growing cybersecurity company, the curve is the evolution of cyberattacks and the products and services that proactively address them. As a predictive enterprise environment, we analyze the petabytes of data that pass through our walls daily and we hire the finest minds in data science to build creative predictive analytics and data science solutions for a myriad of business problems.
We’re trailblazers that dream big, take risks, and challenge cybersecurity’s status quo. It’s simple: we can’t accomplish our mission without diverse teams innovating, together. To learn more about our dedication to inclusion and innovation, visit our Life at Palo Alto Networks page and our diversitywebsite.
Palo Alto Networks is an equal opportunity employer. We celebrate diversity in our workplace, and all qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or other legally protected characteristics.
Additionally, we are committed to providing reasonable accommodations for all qualified individuals with a disability. If you require assistance or accommodation due to a disability or special need, please contact us at email@example.com.