Senior Professional Services Engineer, Actimize

So, what’s the role all about?

We are seeking a skilled Senior Data Engineer to join our Actimize Watch Data Analytics team. In this role, you will collaborate closely with the Data Science team, Business Analysts, SMEs to monitor and optimize the performance of machine learning models.

You will be responsible for running various analytics on data stored in S3, using advanced Python techniques, generating performance reports & visualization in Excel, and showcasing model performance & stability metrics through BI tools such as Power BI and Quick Sight.

How will you make an impact?

1. Data Integration and Management:

• Design, develop, and maintain robust Python scripts to support analytics and machine learning model monitoring.
• Ensure data integrity and quality across various data sources, primarily focusing on data stored in AWS S3.
• Check the data integrity & correctness of various new customers getting onboarded to Actimize Watch

1. Analytics and Reporting:

• Work closely with Data Scientists, BAs & SMEs to understand model requirements and monitoring needs.
• Perform complex data analysis as well as visualization using Jupyter Notebooks, leveraging advanced Python libraries and techniques.
• Generate comprehensive model performance & stability reports, showcase them in BI tools.
• Standardize diverse analytics processes through automation and innovative approaches.

1. Model Performance Monitoring:

• Implement monitoring solutions to track the performance and drift of machine learning models in production for various clients.
• Analyze model performance over time and identify potential issues or areas for improvement.
• Develop automated alerts and dashboards to provide real-time insights into model health.

1. Business Intelligence and Visualization:

• Create and maintain dashboards in BI tools like Tableau, Power BI and QuickSight to visualize model performance metrics.
• Collaborate with stakeholders to ensure the dashboards meet business needs and provide actionable insights.
• Continuously improve visualization techniques to enhance the clarity and usability of the reports.

1. Collaboration and Communication:

• Work closely with cross-functional teams, including Data Scientists, Product Managers, Business Analysts and SMEs  to understand requirements and deliver solutions.
• Communicate findings and insights effectively to both technical and non-technical stakeholders.
• Provide support and training to team members on data engineering and analytics best practices and tools.

Have you got what it takes?

• 5 to 7 years of experience in data engineering, with a focus on analytics, data science and machine learning model monitoring.
• Proficiency in Python and experience with Jupyter Notebooks for data analysis.
• Strong experience with AWS services, particularly S3 and related data processing tools.
• Expertise in Excel for reporting and data manipulation.
• Hands-on experience with BI tools such as Tableau, Power BI and QuickSight.
• Solid understanding of machine learning concepts and model performance metrics.
• Strong Python & SQL skills for querying and manipulating large datasets.
• Excellent problem-solving and analytical skills.
• Ability to work in a fast-paced, collaborative environment.
• Strong communication skills with the ability to explain technical concepts to non-technical stakeholders.

Preferred Qualifications:

• Experience with other AWS services like S3, Glue as well as BI tools like QuickSight & PowerBI
• Familiarity with CI/CD pipelines and automation tools.
• Knowledge of data governance and security best practices.

What’s in it for you?

Join an ever-growing, market disrupting, global company where the teams – comprised of the best of the best – work in a fast-paced, collaborative, and creative environment! As the market leader, every day at NiCE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NiCEr! 

Enjoy NiCE-FLEX!

At NiCE, we work according to the NiCE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere. 

Requisition ID: