Senior Data Science Engineer

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November 25

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Knowledge Anywhere

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SaaS • Education • Enterprise

Knowledge Anywhere is a provider of a feature-rich Learning Management System (LMS) designed to streamline and enhance corporate training programs. The company offers a centralized platform that allows businesses to create, manage, and track training courses for employees, customers, or partners. The LMS includes advanced features such as assessments with AI, badges & leaderboards, course conversion tools, and reporting & analytics, among others. Knowledge Anywhere caters to various industries such as financial services, healthcare, manufacturing, and more. They also provide custom course development, a large course library, and virtual reality training solutions to meet diverse training needs. With a focus on compliance, employee onboarding, and talent development, Knowledge Anywhere aims to improve training efficiency and drive organizational growth.

11 - 50 employees

Founded 1998

☁️ SaaS

📚 Education

🏢 Enterprise

📋 Description

• Work back from the business problems to be solved, collect proper data to do statistical analysis, select proper machine learning and/or deep learning modeling approaches, eventually rollout ML models in production environment to perfect business decision. • Coach junior associates during project collaborations. • Understand business needs and explore appropriate data sources - be curious and proactive in exploring and understanding data. • Perform data aggregation, and feature engineering needed; write Python programming code to make visualizations, build, validate, and implement models. • Collaborate with other data scientists and engineers. • Be flexible and open to innovative ideas and alternative ways of solving problems. • Be able to clearly communicate with and present the results to non-tech partners.

🎯 Requirements

• Master's degree (or higher) in Statistics, Data Science, Mathematics, Economics or related analytical discipline. • At least one years’ experience in building end-to-end models in python (or similar language) through production. This requirement can be omitted for Ph.D. degree holders. • Proficiency in SQL and Python programming languages (pandas, numpy, scipy, scikit-learn, etc.) • In-depth understanding of statistical knowledge and machine learning algorithms. Exposure and some deep learning knowledge are required. • Specifically, expertise with the following techniques are must-haves to perform daily work: Linear Regression and GLM, GBM, Random Forest, XGboost, segmentation techniques, etc. Knowledge on Large Language Models and Neural Networks are nice to have. • Effective communication skills. • Ability to learn new skills and independently take on tasks.

🏖️ Benefits

• EOE including disability/veteran • At Anywhere, compensation varies by knowledge, skills, and experience. Bonuses, incentives and benefits, depend on the position