Data Science Engineer

Responsibilities

• Collaborating with internal stakeholders and data owners to define business problems and structure data for machine learning applications, including customer churn prediction and renewal likelihood modeling.
• Applying deep understanding of Natural Language Processing (NLP), including transformer-based models and attention mechanisms, to extract business-relevant signals such as customer sentiment, intent, and urgency from case descriptions and support conversations.
• Developing chatbot applications using large language models (LLMs) and Qlik’s internal knowledge resources to automatically retrieve and summarize answers from historical customer support case data.
• Designing and training supervised learning models on structured and unstructured data to extract insights from customer support cases and improve operational decision-making.
• Building and validating predictive models using tools such as Qlik AutoML and Python-based machine learning libraries (e.g., scikit-learn, XGBoost, Hugging Face Transformers).
• Guiding technical and non-technical users through the process of creating datasets and using predictive analytics tools to forecast key business metrics.
• Developing and deploying descriptive and predictive analytics dashboards using Qlik Sense.
• Writing and optimizing SQL queries and performing complex data engineering tasks to transform large datasets for analytics and machine learning readiness.
• Providing technical feedback to engineering and product teams, contributing to feature improvements and customer success for Qlik AutoML.
• Educating customers on the adoption and effective use of Qlik’s machine learning product through hands-on guidance and tailored walkthroughs.
• Training internal teams on core machine learning concepts, tools, and best practices to support customer-facing roles and internal development.

Work remotely from anywhere in U.S. Salary $75-125K/year.

Bachelor’s degree in computer science, computer engineering, or mathematics. Six months of part-time or full-time experience as a Data Science Engineer, Research Assistant, Teaching Assistant, or related, or one university course in the following (may be concurrent with degree):

• Machine learning, modeling, and prediction tasks
• Natural Language Processing (NLP), including transformer models, attention mechanisms, and large language models (LLMs)
• Python programming and development of end-to-end machine learning workflows, including model design, training, evaluation, and deployment
• Data processing
• Algorithms and systems programming