Description

Lead Data Scientist

Electronic Merchant Systems (EMS) is a leading provider of payment processing and merchant services. Since 1988, EMS has been helping business owners realize their full potential and grow their financial well-being. We’re headquartered in beautiful Cleveland, Ohio, with offices and agents coast to coast serving tens of thousands of retail, internet, and start-up businesses. No matter where you are, EMS is never far away.

EMS’ mission is to be the industry-leading merchant services provider that empowers merchants to increase their financial well-being. Our innovative suite of business solutions, high-quality service, and professional, dedicated employees are the driving force behind the success of this mission.

General Function:

We are seeking a highly skilled Data Scientist with a strong background in data reporting, statistical modeling and machine learning to join our dynamic team. The ideal candidate will be responsible for developing predictive models, performing data analysis, and providing actionable insights to drive risk business decisions.

Duties and Responsibilities:

• Model Development: Design, build, and validate risk models using statistical, machine learning, and deep learning techniques.
• Data Analysis: Conduct data analysis to understand risk performance, data patterns and provide actionable insights.
• Feature Engineering: Create and select appropriate features to enhance model performance.
• Data Collection and Cleaning: Collect, clean, and preprocess data from various sources to ensure high-quality datasets for analysis.
• Performance Monitoring: Monitor and assess the performance of risk activities, alongside deployed models and provided recommendations to improve as necessary.
• Collaboration: Work closely with cross-functional teams including risk leaders, finance, and other stakeholders to understand requirements and deliver data-driven solutions.
• Reporting and Visualization: Develop and present detailed reports and visualizations to communicate performance, findings and recommendations to non-technical stakeholders.
• Innovation: Stay updated with the latest advancements in data science and modeling techniques and apply them to solve business problems.

Qualifications

• Education: Master’s or Ph.D. in Data Science, Statistics, Computer Science, Mathematics, or a related field.
• 3 years of experience in data science and modeling.
• Proven experience in developing and deploying machine learning models in a production environment.
• Technical Skills:
• Proficiency in programming languages such as Python or R.
• Strong knowledge of SQL and experience with databases.
• Familiarity with data visualization tools (e.g., Tableau, Power BI, matplotlib).
• Analytical Skills: Strong analytical and problem-solving skills with the ability to interpret complex data and generate actionable insights.
• Communication Skills: Excellent verbal and written communication skills with the ability to explain complex concepts to non-technical audiences.
• Team Player: Ability to work effectively in a team environment and collaborate with various stakeholders.

Preferred Qualifications:

• Experience supporting a Payments Risk function
• Experience with big data technologies (e.g., Hadoop, Spark).
• Knowledge of cloud platforms (e.g., AWS, Google Cloud, Azure) and related data services.