Senior Data Scientist

About the Role

Key Responsibilities

• Developing ML/AI/GenAI models and solutions.
• Performing data gathering, data mining, and data processing on large volumes of data; creating appropriate data models.
• Demonstrating a breadth of knowledge in the application of ML/AI/GenAI and statistical methods and/or digital methods to solve business problems.
• Conducting research on data model optimization and algorithms to improve the effectiveness and accuracy of data analyses.
• Interacting and collaborating with team members and colleagues outside the organization, including outside of IT organization.
• Participating on 1-2 projects concurrently.
• Having a strong focus on continual learning in the Analytics field.

Requirements

• Extensive knowledge of techniques and tools for effective analysis; ability to determine the root cause of problems and create alternative solutions.
• Working experience and knowledge of the principles, technologies, and algorithms of GenAI, AI, and machine learning; ability to develop, implement, and deliver related systems, products, and services.
• Extensive knowledge of statistical tools, processes, and practices to describe results on measurable scales; ability to use statistical tools and processes to assist in making business decisions.
• Working experience in applying Python (NumPy, SciPy, Pandas, etc.) to solve business challenges; ability to use tools, techniques, and platforms to write and modify programming languages.
• Experience in processing large quantities of detailed information with high levels of accuracy.
• Working knowledge in writing, debugging, and implementing complex queries involving multiple tables or databases.
• Strong presentation and communication skills.
• Typically, a Bachelor's, Master's, or Ph.D. degree in a quantitative field such as statistics, economics, mathematics, or similar.
• Professional experience utilizing quantitative analysis, or a Master's degree with 5+ years of experience, or Ph.D. with 2+ years of experience.
• Experience with data analysis and statistical methods such as regression, hypothesis testing, ANOVA, statistical process control.
• Practical applications of machine learning techniques such as clustering, logistic regression, CART, random forests, SVM, or neural networks.
• Knowledge of cloud technologies (AWS, Azure, Google Cloud).
• Experience operating in an Agile environment.
• Strong initiative, interpersonal skills, and effective communication abilities.

Nice to Have

• Experience connecting data from various business domains and providing forecasts and insights.
• Working knowledge of version control/repositories such as GitHub.
• Experience with projects involving digital methods to solve business problems.
• Ability to research and apply new methods and digital technologies to exceed customer expectations.

Qualifications

• Typically, a Bachelor's, Master's, or Ph.D. degree in a quantitative field such as statistics, economics, mathematics, or similar.
• Professional experience utilizing quantitative analysis, or a Master's degree with 5+ years of experience, or Ph.D. with 2+ years of experience.

Benefits & Perks

• Medical, dental, and vision benefits.
• Paid time off (Vacation, Holidays, Volunteer).
• 401(k) savings plans.
• Health Savings Account (HSA).
• Flexible Spending Accounts (FSAs).
• Health Lifestyle Programs.
• Employee Assistance Program.
• Voluntary Benefits and Employee Discounts.
• Career Development.
• Incentive bonus.
• Disability benefits.
• Life Insurance.
• Parental leave.
• Adoption benefits.
• Tuition Reimbursement.