Secureworks® (NASDAQ: SCWX) a global cybersecurity leader, enables our customers and partners to outpace and outmaneuver adversaries with more precision, so they can rapidly adapt and respond to market forces to meet their business needs. With a unique combination of cloud-native, SaaS security platform and intelligence-driven security solutions, informed by 20+ years of threat intelligence and research, no other security platform is grounded and informed with this much real-world experience. www.secureworks.com
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.
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.
The ideal candidate should be comfortable identifying problems that involve data driven solutions, exchanging with stakeholders and giving technical presentations on both theoretical and practical specifics of machine learning algorithms and analytic methodologies. The candidate must be able to work effectively in a distributed, startup-like, collaborative team of product managers, software engineers, and security researchers.
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 by having continuous conversation with the stakeholders.
Research the latest algorithms and academic techniques and present them to the team.
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.
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 and a willingness to learn other technologies.
Experience with problems and projects that depart from your average academic or Kaggle project and address real-world issues like severe class imbalance and data drifts.
Foundational knowledge of statistics and how it can be applied to extract knowledge from data sets, monitor data sources and assess machine learning models.
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 and tradeoffs and tradeoffs of various architectural approaches when applied to machine learning algorithms when confronting complex, high-volume, high-dimensionality data from varying sources.
Ability to frame data science problems correctly and work in an iterative way to arrive at an optimal solution.
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.
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.
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 Secureworkshere.