Senior Data Science Engineer

About Nintex:

At Nintex, we are transforming the way people work, everywhere. As the global standard for process intelligence and automation, we're trusted by over 10,000 public and private sector organizations across 90 countries. Our customers, from industry giants like Amazon, Coca-Cola, and Microsoft, rely on the Nintex Platform to accelerate their digital transformation journeys by managing, automating, and optimizing business processes quickly and efficiently. We improve their lives through the technology we build.

We are committed to fostering a workplace that supports amazing people in doing their very best work every day. Collaboration is constant, our workplace is fun, the environment is fast-paced, and we value our people’s curiosity, ideas, and enthusiasm. Driven by passion and accountability, we take initiative, measure progress, and deliver results. Our culture fosters innovation and problem-solving, fueled by curiosity and a commitment to thinking big. Together, we move with agility, prioritize customer needs, and build unity through empathy, leaving a positive impact wherever we go.

Working in engineering:

Working at Nintex as an engineer means building more than just software; it’s about making a tangible impact with every line of code. Our engineers are process experts, developing the industry’s most complete process and automation platform to transform the way people work. If you’re interested, curious and want to learn and do more, the sky is the limit here. We take a solutions-oriented and collaborative approach, constantly innovating our business and products.

About the role:

We are looking for a highly skilled and versatile Data Scientist/Data Engineer to join our team. The ideal candidate will have a strong technical background, be proficient in Python, and have experience managing data pipelines and using technologies like Docker, RabbitMQ, SQLite, and more.

Your contribution will be:

Data Science and Engineering:

• Develop and implement advanced data science models.
• Design and optimize data pipelines for various AI features across our product suite.
• Utilize Python and its major libraries (Pandas, Scikit-learn, NumPy, etc.) to analyze and process large datasets.

Product Mastery:

• Gain deep knowledge of our various AI or generative AI features across our products.
• Work closely with the product development team to integrate advanced data science methodologies into our products.

Pipeline Management:

• Design, build, and maintain scalable data pipelines that ensure smooth operation across various products.
• Optimize data processing workflows using tools like Docker, RabbitMQ, and SQLite.
• Monitor and troubleshoot data pipelines, ensuring data integrity and performance.

Collaboration and Implementation:

• Collaborate with cross-functional teams, including software developers, data analysts, and product managers, to deliver high-quality solutions.
• Implement and deploy machine learning models and data processing algorithms across various products.

Continuous Improvement:

• Continuously seek ways to improve the accuracy and efficiency of data processing across our various products.

Stakeholder Communication:

• Communicate complex data insights to non-technical stakeholders in a clear and concise manner.

Research:

• Stay up-to-date with the latest technology trends and techniques in data science, and implement new methodologies as appropriate.

To be successful, we think you need:

• 3+ years of experience in data science and data engineering roles.
• Strong proficiency in Python and major libraries such as Pandas, Scikit-learn, NumPy, TensorFlow, etc.
• Experience with ML libraries: TensorFlow, PyTorch or similar.
• Proven experience in building and managing data pipelines using Docker, RabbitMQ, and SQLite.
• Experience with SQL and database management.
• Strong problem-solving skills and the ability to work both independently and collaboratively.
• Preferred:
• Experience with generative AI technologies.
• Familiarity with containerization and orchestration tools like Kubernetes.
• Experience with cloud platforms like AWS, Azure, or Google Cloud.
• Experience with ML Flow or DataBricks ML highly advantageous.

What’s in it for you?

Our people work in the way that best suits them and their teams - whether at home, in an office, or another place that sparks creativity, focus, and collaboration. Our work environment is such that our people can successfully deliver their work while adequately supporting their lifestyle and preferences.

While our offerings differ from country to country, we offer our entire global workforce an array of exciting perks and benefits, including:

• Global Gratitude and Recharge Days
• Flexible, paid time off policy
• Employee wellness programs and counseling resources
• Meaningful peer recognition and awards
• Paid parental leave
• Invention/patenting assistance
• Community impact, paid volunteer time, and opportunities
• Intercultural learning and celebration
• Multiple tools through which to learn and grow, and an incredible global community

View more about our benefits here: Benefits.

Equity Statement: Preference will be given to People Living with Disability who are members of the designated groups in line with the Employment Equity Plan and Targets of the Company.