Data Science Engineer

Data Science Engineer

Remote job in the United States. Salary: $75-125K/year. Job Category:
Customer Success.

Data Science Engineer remote role focused on applying machine learning and data science techniques to support customer success initiatives, build predictive models, and develop analytical dashboards.

• Collaborate 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.
• Apply 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.
• Develop chatbot applications using large language models (LLMs) and internal knowledge resources to automatically retrieve and summarize answers from historical customer support case data.
• Design and train supervised learning models on structured and unstructured data to extract insights from customer support cases and improve operational decision-making.
• Build and validate predictive models using tools such as Qlik AutoML and Python-based ML libraries (e.g., scikit-learn, XGBoost, Hugging Face Transformers).
• Guide technical and non-technical users through the process of creating datasets and using predictive analytics tools to forecast key business metrics.
• Develop and deploy descriptive and predictive analytics dashboards using Qlik Sense.
• Write and optimize SQL queries and perform complex data engineering tasks to transform large datasets for analytics and machine learning readiness.
• Provide technical feedback to engineering and product teams, contributing to feature improvements and customer success for Qlik AutoML.
• Educate customers on the adoption and effective use of Qlik's machine learning product through hands-on guidance and tailored walkthroughs.
• Train internal teams on core machine learning concepts, tools, and best practices to support customer-facing roles and internal development.

• 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