ControlUp creates an autonomous workplace where the day runs itself.
We’re a leader in DEX, unifying digital employee experience and IT operations into one powerful platform built for modern workplace management. By combining real-time monitoring, automation, and proactive remediation, ControlUp enables IT teams to prevent issues before they impact employees, reduce operational complexity, and streamline IT environments, without the clutter of multiple tools. With ControlUp, IT works smarter, employees stay productive, and the workday runs itself. One platform. One powerful shift in how work flows.
No tool sprawl. No wasted time. No interruptions. Just technology that runs smoothly, so people can get on with work that matters.
The Role
We’re looking for a
Senior Data Scientist to join our team and drive data-powered decision making across products, operations, and strategy. In this role, you’ll work at the intersection of machine learning, large-scale data analysis, and product innovation—translating complex business problems into scalable, data-driven solutions.
You’ll collaborate closely with engineering, product, and business stakeholders to uncover insights, optimize performance, and help shape the future of our data science capabilities.
How You’ll Spend Your Day
- Assume ownership of multiple AI/ML solutions and features research and deliver value to our customers
- Conduct data discovery of big data sources to identify potential applications and address specific problems
- Design, implement, and guide end-to-end machine learning pipelines
- Think creatively about complex problems and deliver technological Innovation
- Statistical Analysis and Modeling: Apply statistical methods and mathematical models to identify patterns, trends, and relationships in data sets, and develop predictive models
- Machine Learning: Develop and implement machine learning algorithms, such as classification, regression, clustering, with classic ML methods (SVM, knn, random forest, XGBoost, logistic regression, etc..) and deep learning, to solve business problems and improve processes
- Feature Engineering: Extract relevant features from structured and unstructured data sources, and design and engineer new features to enhance model performance
- Model Development and Evaluation: Build, train, and optimize machine learning models and evaluate model performance using appropriate metrics
- Data Visualization: Present complex analysis results in a clear and concise manner using data visualization techniques, and communicate insights to stakeholders effectively
- Collaborative Problem-Solving: Collaborate with cross-functional teams, including product managers, data engineers, software developers, and business stakeholders to identify data-driven solutions and implement them in production environments
Your Experience And Qualifications
- M.Sc. in Computer Science, Engineering, or Mathematics. 6+ years expertise driving multiple and scalable ML solutionsExperience in data science tools and libraries such as PyTorch/TensorFlow/KerasSolid foundation in statistical concepts and techniques, including hypothesis testing, regression analysis, time series analysis, and experimental designExperience in data visualization and data exploration to create meaningful representations of dataExperience working with Big data technologies such as Kafka/Spark/OpenSearch, Parquet/protobuf/Avro/Splunk/ELK stack.Good knowledge in GenAI tools such as LLM Orchestrations and integration packages, Agents, RAG systemsStrong communication and collaboration skillsDemonstrated ability to work effectively alone and in cross-functional teams, collaborate with colleagues, and contribute to a positive work environment
- Experience in the IT domain - an advantage
- Strong analytical and critical thinking skills to approach business problems, formulate hypotheses, and translate them into actionable solutions - an advantage
- Experience with Azure Devops, PySpark, Docker and K8S - an advantage