Lead Data Scientist

Come work at a place where innovation and teamwork come together to support the most exciting missions in the world!

We are seeking a Lead Data Scientist to help build next generation Security Analytics product from ground-up. 
Working with a team of engineers and architects, you will be responsible for prototyping, designing, developing and supporting a highly scalable SaaS based Security Analytics product. 
This is a great opportunity to be an integral part of a team building Qualys’ next generation Micro-Services based technology platform processing over a 100 million transactions and terabytes of data per day, leverage open-source technologies, and work on challenging and business-impacting projects. 
We are looking for Data Scientist, who will support our Research and Development team with insights gained from analyzing security data.
The ideal candidate has background in a quantitative or technical field, is adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action.
They must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations. You are focused on results, a self-starter, and have demonstrated success for using analytics to drive the understanding, growth, and success of a product.

Responsibilities: 

• Minimum Masters/PhD(preferred) in CS/IT/Operations Research/AI or Data Science (preferred), from top tier colleges (IISc / IITs-old 5 /IIIT / ISI Cal /NITs), lets avoid any other specializations.
• Published research papers in top international journals/conference related to cybersecurity or AI/ML applied to tech problems.
• 6-8 years of professional experience in tech-domains such as security, cloud, virtualization, storage, networking, etc. Research experience is fine if it’s in cybersecurity related AI/ML from top tier institution/lab.
• Hands on with Python: Pytorch, Tensorflow, Scikit learn, LLM, Boosting algorithms, NLP, Model explainability, etc. and Apache Spark (must have).
• Aware of distributed system design – streaming, batch, microservices, Kubernetes, MLOPs and design tradeoffs.
• Ready/wants to contribute rather than advice : 95% hands on + 5% coordination/planning role.
• Responsibilities: Work with DS team, Product managers and other stakeholders:
  • Define the problem and success criteria.
  • Do extensive literature survey including competitive analysis (with PMs)
  • Build POC/working prototype with other members in DS team.
  • Lead and contribute to the data creation/collection, curation and labelling to train ML models.
  • Understand Qualys platform/architecture and build ML solution architecture working with other engineering teams.
  • Work hand in hand with data engineers to build data processing pipelines and automated CI/CD (model training and deployment) pipelines.
  • Plan and coordinate the rollout of ML models to production with MLOPs/Infra teams.
  • Lead, mentor other junior team members : Identify their skill gaps and work with them to bridge those in timely manner.
  • Review code, data and other artefacts produced by DS team.
  • Over time develop in depth understanding of the cybersecurity industry in which Qualys operates and evangelize on how AI/ML approaches can help.