Join our team and experience Workday!
It's fun to work in a company where people truly believe in what they're doing. At Workday, we're committed to bringing passion and customer focus to the business of enterprise applications. We work hard, and we're serious about what we do. But we like to have a good time, too. In fact, we run our company with that principle in mind every day: One of our core values is fun.
The perfect candidate will have a background in a quantitative or technical field, will have experience working with large data sets, and will have some experience in data-driven decision making. You are focused on results, a self-starter, and have demonstrated success in using analytics to drive the understanding, growth, and success of a product. This full time position is based in our Headquarters in Pleasanton, CA.
* Apply your expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and understand and mitigate the threat to our customers, product and company.
* Our Threat Intel Data scientists ideally possess deep knowledge of advanced threat actors, including their tactics, techniques, and procedures, as well as an understanding of the overall threat landscape and geopolitical climate. Using this knowledge, we leverage a variety of data sources including internal data, open-source intelligence, and third party private intelligence to detect and track adversary groups both on and off the Workday platform. In order to be successful, our scientists must be able to tirelessly explore and get intimate with collected data; and research, define, test and refine classification models to not only track known activity but also to surface previously unidentified activity and develop novel and effective strategies to disrupt attackers.
We look for people who have a strong desire to solve complex problems and develop new solutions, often involving collaboration with different teams across the company. Necessary skills include competence with Python, SQL, and data science, as well as a background in producing threat intelligence products
* Partner with Product and Engineering teams to solve problems and identify trends and opportunities. Meaningfully visualize the models and their effectiveness; Design, implement, deploy and support production Microservices and Data Pipelines;
* · Day to Day job of the Data scientist involves but not limited to:
* Lead quantitative analysis projects from start to finish including all aspects of data analysis (e.g. processing, cleaning, verifying the integrity of data used for analysis, statistical analysis, visualizations) and communicating results
* Building Machine Learning models of user behaviors for threat analysis
* Influencing product teams through presentation of data-driven recommendations
* Working in Hadoop, Hive, REDIS, My SQL, S3
* Automating analysis and authoring pipelines via SQL, R, Python, H20, Apache Flink, Spark, Splunk, Amazon Sagemaker
* The ideal candidate will at minimum have experience in the following areas:
* Undergrad or Masters or PhD degree in Computer Science, Math, Physics, Engineering, Statistics or other technical field
* Experience with distributed computing (Hive/Hadoop)
* 3+ years experience doing quantitative analysis
* 10+ years of Technical experience in building large scale applications
* Knowledge of statistics (e.g., hypothesis testing, regressions)
* Advanced knowledge of Python, in particular packages such as Pandas, Numpy, SciPy, Matplotlib (or equivalent). Knowledge of PySpark/Scala is a bonus
* Practical understanding of SQL and NoSQL databases
* Experience selecting, developing and refining machine-learning models
* Demonstrable proficiency in statistical data analysis and data visualization
* Confidence to build relationships with both internal teams and external vendors, and ability to communicate effectively with both technical and non-technical audiences
* Contributions to Open Source repositories is a plus.
Workday is a company providing enterprise cloud applications for finance and human resources.