Job Location: Pune
We are seeking a Principal 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 conducting research on leveraging data science for existing and new products, 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 Machine Learning and Deep Learning models to test the effectiveness of different courses of action.
They must have strong experience using a variety of machine learning/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:
You will evaluate and make decisions regarding the use of new or existing machine learning algorithms and tools, as well as influence other Engineering Leaders, Product Managers, and their teams to build the right systems and employ the right machine learning solutions.
Conduct the literature survey, implement machine learning algorithms and evaluate their performance.
Develop novel machine learning algorithms to predict malicious content or activity using data in various formats including text and tabular data.
Coordinate the integration of machine learning solutions among development teams to ensure system performance, security, scalability and availability.
Designing and deploying Machine Learning Algorithms – both Shallow learning models and Deep learning models.
Develop processes and tools to monitor and analyze model performance and data accuracy.
Collaborate with data and subject matter experts throughout the organization to identify opportunities for leveraging data to drive business solutions.
Understand the Distributed Ecosystem/Cloud computing services and deploy ML models on the same.
You will present the results of the team’s research in conferences in the field of machine learning in cybersecurity.
Coaching and mentoring junior team members and evolving team talent pipeline.
Qualifications:
6 years of work experience in the machine learning or data science field with MS or PhD or 10 years of experience with BS in Computer Science, Electrical Engineering, Operations Research, Mathematical Modeling & Simulation, Statistics, or equivalent fields. Specialization in machine learning or data science is preferred.
Deep understanding of mathematical foundations of machine learning, including statistics, linear algebra, and computer science.
Prior publications in peer-reviewed journals or conferences in machine learning or cybersecurity.
Experience in cutting-edge areas such as Machine Learning, Deep Learning, Stream Processing, MLOps, In-Memory Computing.
Experience with Natural Language Processing (NLP) libraries and tools such as Spark NLP, Hugging Face, NLTK, Spacy, Labelling Studio, etc.
Experience with data cleansing, data engineering, data quality assessment, and using analytics for data assessment.
Hands on Experience in Data science programming skills – Python, R, Java, Scala.
Proven work experience of a variety of machine learning techniques (supervised and unsupervised machine learning algorithms such as SVM, random forest, PCA, t-SNE, clustering, and neural networks) and their real-world advantages/drawbacks.
Experience of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
Having experience in developing some use cases related to Cyber Security.
Familiarity with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Flink, Spark, Cassandra, etc.
Hands on experience with Keras/Tensorflow/PyTorch/SciKit Learn.
Practical experience with ML Operations tooling including MLflow, Sagemaker, or Databricks.
Experience in visualizing/presenting data for stakeholders using: Matplotlib, seaborn, ggplot or any data visualization tool.
Work along with Senior and Stake holders to capture the requirements and execute it in Agile methodology.
Strong interpersonal and leadership skills, as well as effective communication (both written and verbal) skills and the ability to present complex ideas to a variety of audiences in a clear and concise manner.
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