Data Scientist / ML Engineer (AWS) for Fitness Studio Business

Project Description: 

We are looking for a Data Scientist / Machine Learning Engineer to develop and implement an ML solution that predicts key business metrics for fitness studios (sales, visits, contract signings, customer indicators) based on historical data. The project will be deployed on AWS.

iKizmet (www.ikizmet.com) is a fast-growing analytics software company specializing in the health and fitness industry. We are integrated with the largest POS and Scheduling platforms in our industry and our client list has some of the largest brands in the boutique fitness space. 

Job Title: Data Scientist / ML Engineer (AWS) for Fitness Studio Business Forecasting Project

Responsibilities: 

• Analyze data from fitness studios: sales, visits, contracts, and customer data. 

• Build end-to-end ML pipelines (data preprocessing → model training → testing → deployment → monitoring). 

• Develop forecasting models (regression, classification, time series). 

• Implement data pipelines and ML workflows on AWS (SageMaker, S3, Glue, Lambda). 

• Set up model performance monitoring and reporting. 

• Prepare reports and visualize results for business stakeholders. 

• Collaborate with team members and stakeholders to align tasks and communicate results. 

Requirements: 

• 3+ years of experience as a Data Scientist / ML Engineer. 

• Strong Python skills (pandas, numpy, scikit-learn, PyTorch or equivalent). 

• Experience with ETL pipelines and working with large datasets. 

• Hands-on experience with time series, regression, and classification models. 

• Proven experience with AWS: SageMaker, S3, Glue, Lambda, CloudWatch. 

• Proficiency in SQL. 

• Ability to clearly explain technical solutions to business stakeholders. 

• English proficiency (Intermediate or higher) for working in an international environment. Nice to have: 

• Experience building BI dashboards (e.g., AWS QuickSight, Power BI, Tableau). 

• MLOps and CI/CD experience. 

We offer: 

• Work on a real-world ML project with impactful business data. • Collaboration with an international team. 

• Flexible schedule, fully remote work. 

• Opportunities for learning, professional growth, and career development. 

Working hours: 11 AM - 7 PM CET

Please let me know if you are interested in our offer.