Data Scientist

• Develop analytics to address an organization's business or Engineering problems.

• Collaborate with Data Engineers to translate Machine Learning algorithms into effective solutions.

• Work in technical teams in development, deployment, and application of applied analytics, predictive analytics, and prescriptive analytics.

• Perform exploratory and targeted data analyses using descriptive statistics and other methods to identify security patterns and anomalies.

• Design and implement analytics pipelines leveraging MLOps practices.

• Collaborate with data engineers on data quality assessment, data cleansing, and the development of operational data pipelines.

• Contribute to data engineering efforts to refine data infrastructure and ensure scalable, efficient analytics.

• Generate reports, annotated code, and other projects artifacts to document, archive, and communicate your work and outcomes.

• Share and discuss findings with team members practicing SAFe Agile delivery model.

Must-HaveSkills:

• Master's / Bachelors degree and 3 to 5 years of experience with one or more analytic software tools or languages (e.g., SAS, SPSS, R, Python) OR

• Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn)

• Outstanding analytical and problem-solving skills; Ability to learn quickly; Excellent communication and interpersonal skills

• Experience with data engineering and pipeline development

• Experience in analyzing time-series data for forecasting and trend analysis

• Experience with AWS, Azure, or Google Cloud

• Experience with Databricks platform for data analytics and MLOps

• Experience with Generative AI models (e.g., GPT, DALLE, Stable Diffusion) and their applications in cybersecurity and data analysis

• Experience working in Product team's environment

• Experience working in an Agile environment