Primary Duties and Responsibilities:

• Maintain and debug the existing web applications and develop new features or applications.
• Perform DevOps tasks and design CI/CD pipelines for the products designed by the broader data science and machine learning team.
• Design and build new programs (e.g. API, UI) to host business models or reports.
• Look for opportunities to enrich team’s best practices with documenting and formatting our repos
• Take ownership of the deployment and QA process. Work with ITS and DevOps team to improve current architecture or build new better ones.
• Ensure data security/privacy and protocols are established and followed based on company and project requirements.
• Work with Git, TFS, Azure, data bricks, and other components of our ecosystem efficiently. Contribute to and maintain the ecosystem to enable the larger team to leverage these data science products/packages for their needs
• Work closely with other analytics team members and business unit’s leaders to drive common goal achievement and organizational objectives. You will be expected to actively engage with partners to design and build solutions that best fit their needs.
• The successful applicant should have a diverse skill set including a strong background in system design, machine learning, and performance, an understanding of accelerator architectures and a passion to design and develop industry leading solutions.

Minimum Qualifications:

• 3+ year of experience with bachelor’s degree in Computer Science, Computer Engineering or other quantitative field, preferably working in a data science or ML/AI centric role; or
• 1-3 year of experience with Masters in above mentioned quantitative fields
• At least 3 years of experience of using python and SQL in professional setting. You should be passionate about writing code with quality and using automation at its best

• Proficient in Python web application stacks (like Django or Web2Py or Flask - preferred) and associated ecosystems
• Direct experience with handling repos in Git/TFS and setting up unit tests for model/application
• Proficient in system analysis & design
• Experience with public cloud services and cloud-native applications, e.g. AWS, Azure (preferred)
• Experience with common data science toolkits, such as R, Python, Caret, PySpark, NumPy, etc. Excellence in more of these is highly desirable
• You prefer driving decisions based on data presented to you and should have good communication skills

Preferred Qualifications:

• Intimate familiarity with Python Flask, API design and development
• Develop clear and concise documentation for delivered tools to ensure proper support from other team’s members