Data Scientist

About the Role

We are seeking a talented Data Scientist to join our Product Analytics team. 
 

This role involves leveraging analytical expertise and machine learning skills to develop predictive models and innovative data-driven solutions. Your contributions will have a direct impact on critical areas such as pricing optimization, customer segmentation, and expert matching. If you are passionate about applying AI to solve real-world challenges and driving meaningful business outcomes,

What You’ll Do:

• As an individual contributor, provide analytical thought leadership to drive strategy, suggest new analyses, statistical/ML frameworks, testing methods and infrastructure improvements to drive value for the business.
• Collaborate with stakeholders to define problem statements, develop new signals using JA data incl. conversational data, develop hypotheses and translate them into analytical solutions and actionable insights presented to wider audiences.
• Perform both Descriptive & Prescriptive Analytics including experimentations (AB, MAB), implement and track trends in business metrics that will help drive the business
• Own outcomes of deep dive analyses, by covering problem definition, metrics development and implementation, data extraction, visualization and presentation to the stakeholders
• Develop machine learning models to solve business problems related to customer segmentation, customer retention, conversation quality, and revenue optimization.
• Become a go to AI/ DS expert who directly and indirectly oversees the model development and advanced statistical work of other analysts.
• Test, validate, and optimize models to ensure performance and scalability.

What We’re Looking For:

• Experience: 2-5 years in data science or product analytics roles focused on model development.
• Technical Skills:
• Proficiency in SQL and Python; experience with BigQuery preferred.
• Strong programming abilities, including familiarity with ML libraries such as TensorFlow, PyTorch, or Keras.
• Hands-on experience with statistical methods and machine learning techniques, including regression, classification, clustering, time series analysis, and frameworks like Naive Bayes, XGBoost, and neural networks.
• Basic knowledge of NLP, computer vision, or reinforcement learning.
• Analytical Expertise: Strong foundation in descriptive and inferential statistical analysis, as well as advanced experimental design.
• Education: Bachelor’s or Master’s degree in a quantitative field such as Data Science, Computer Science, Mathematics, Econometrics, or Statistics.

Preferred Qualifications:

• Experience in e-commerce, product, or retail analytics.
• Proficiency in NLP and text analytics techniques.
• Familiarity with large language models (LLMs) and prompting.

• Understanding of CI/CD pipelines for machine learning model deployment.

   

Perks and Benefits

• Time off throughout the year (paid and unpaid)
• Professional development support and encouragement
• Resources to help improve your overall well-being
• Free membership to dive into JA product