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Principal Data Scientist – Secureworks - Columbia, MD or Remote

Columbia, Maryland

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Job ID R82839 Date posted Jan. 03, 2019

Secureworks (SCWX-NASDAQ) is a global leader in intelligence-driven information security solutions. We help organizations confidently pursue business goals in a digitally-connected world.  Consistently recognized by industry analysts and readers’ polls, we are one of the best in the world at understanding and anticipating threat behavior. We see 250 billion events every day across 4400 clients in more than 55 countries, and our solutions work across all the layers of a client’s security environment, including 330 different vendor technologies. Join a talented, dedicated, and diverse team of researchers, analysts, engineers, consultants and business professionals who are focused 100% on protecting our clients from cyber threats. We seek out the brightest minds and empower our teams with the tools and support they need to fight the bad guys and maintain our company’s leadership in the cyber security industry. 

Uniquely positioned to adapt as the industry evolves, we are also proud to be part of the Dell Technologies family. We enjoy competitive compensation and benefits packages, and reward and recognize our employees for exceptional results. A constant focus on continued learning and growth keeps our team members engaged and excited about “what’s next.” We offer flexible work options when available, and emphasize the importance of work-life balance. We know that when our people are rewarded, recognized, and rejuvenated, we win as a team.

Role Overview

We are looking for a senior data scientist to advance the state-of-the-art in network defense, developing new solutions from research to production on massive, multi-modal data sets. If you’re a data scientist with experience applying machine learning to challenging real-world problems, we need your help to push the boundaries of artificial intelligence and bring the most innovative security products to life.  You will work on the next generation Secureworks platform, demonstrating the power that data science can bring to cyber security.  

Responsibilities

  • Apply data science and machine learning to threat intelligence, network situational awareness, intrusion detection and prevention, incident response, and malware analysis.  
  • Verify and validate the utility of these methods towards definitively improving computer security.
  • Research the latest algorithms and academic techniques and present them to the team.
  • Give technical presentations and discuss both theoretical and practical specifics of machine learning algorithms and analytic methodologies.
  • Prototype new approaches to extract information from large volumes of structured and unstructured data and correlate events across multiple sources.  
  • Collaborate closely with software engineers to productize your prototypes and deploy them in secure, scalable, and fault-tolerant solutions across a distributed architecture.
  • Drive the collection of new data and the refinement of existing data sources including novel ways of getting it labeled.
  • Work effectively in a distributed, startup-like, collaborative team of product managers, software engineers, and security researchers.

Requirements

  • BA/BS degree in Computer Science, Machine Learning, or related technical field.
  • 5+ years of relevant work experience with machine learning or data science.
  • Proficiency in R, Python, and/or Scala.
  • Experience with problems and projects that depart from your average academic or Kaggle project and address real-world issues like severe class imbalance.
  • Excellent understanding of machine learning techniques in high-dimensional spaces including kernels, ensembles, regularization, dimensionality reduction, and clustering.
  • Extensive experience with a variety of machine learning algorithms, ideally with a focus on information security, detection tasks, recommender systems, or natural language processing.
  • Strong understanding of the limitations of various architectural approaches when applied to machine learning algorithms when confronting complex, high-volume, high-dimensionality data from varying sources.
  • Superior verbal and written communication skills, ability to convey rigorous mathematical concepts and considerations to non-experts.
  • Passion about machine learning and a desire to constantly learn as the field evolves.

Preferences

  • MS or PhD degree in Computer Science, Machine Learning, or related technical field.
  • 3+ years developing and deploying machine learning solutions in a production environment.
  • Experience developing end-to-end solutions on big data platforms, such as Hadoop or Spark.
  • Experience with a machine learning library, such as scikit-learn, MLlib, TensorFlow, Caffe/2, Keras, Pytorch/Torch, MxNet, etc.
  • Exposure to packet captures, network flows, log data, malware analysis, a plus.
  • Experience with Amazon AWS, Google GCP, or similar cloud provider.
  • Prior experience working at a startup or in an entrepreneurial environment.

This is a remote position with potential travel up to 5%

Secureworks (A Dell Technologies Company) is committed to the principle of equal employment opportunity for all employees and to providing employees with a work environment free of discrimination and harassment. All employment decisions at Secureworks are based on business needs, job requirements and individual qualifications, without regard to race, color, religion or belief, national, social or ethnic origin, sex (including pregnancy), age, physical, mental or sensory disability, HIV status, sexual orientation, gender identity and/or expression, marital, civil union or domestic partnership status, past or present military service, family medical history or genetic information, family or parental status, or any other status protected by the laws or regulations in the locations where we operate. Secureworks will not tolerate discrimination or harassment based on any of these characteristics.  Learn more about Diversity and Inclusion at Secureworks here.

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