Want to get hired at Tiger Analytics?
Lead Data Scientist - Price Elasticity Modelling
Tiger Analytics
HybridHybrid
Original Job Summary
Overview
Tiger Analytics is looking for experienced Data Scientists to join our fast-growing advanced analytics consulting firm. As a Lead Data Scientist - Price Elasticity Modelling, you will apply your expertise in machine learning, data mining, and information retrieval to design, prototype, and build next-generation advanced analytics engines and services.
Key Responsibilities
- Collaborate with business partners to develop innovative solutions.
- Develop, test, and deploy solutions using Python, SQL, and PySpark on enterprise platforms such as Databricks.
- Translate models into production-ready code in collaboration with a team of data scientists.
- Implement CI/CD pipelines and manage code repositories using GitHub Enterprise.
- Design and optimize mathematical programming and machine learning models for applications like incentive elasticity modeling.
- Implement scenario simulation algorithms and break down complex problems into actionable tasks.
- Ensure code quality, scalability, and maintainability in a production environment.
- Engage in sprint planning, documentation, and cross-functional collaboration.
- Coach and collaborate with a growing team of experienced professionals.
- Stay updated through conferences and community engagements.
Requirements
- 8 years of experience as a Data Scientist.
- Hands-on enterprise data science experience, preferably in retail, inventory management, or operations research.
- Proficient in Python, SQL, and PySpark with experience in Databricks or similar platforms.
- Familiarity with ML libraries such as NumPy, SciPy, scikit-learn, MLlib, PyTorch, and TensorFlow.
- Experience with production-level coding and deployment practices.
- Strong independent work ethic with an ownership mindset.
Key skills/competency
Data Science, Machine Learning, Python, SQL, PySpark, Databricks, CI/CD, Optimization, Modelling, Analytics
How to Get Hired at Tiger Analytics
🎯 Tips for Getting Hired
- Research Tiger Analytics: Understand their analytics approach and clientele.
- Customize your resume: Highlight Python, SQL, and PySpark skills.
- Prepare for technical interviews: Review machine learning and optimization topics.
- Showcase project experience: Provide examples of elasticity modelling projects.
📝 Interview Preparation Advice
Technical Preparation
circle
Study Python and SQL syntax.
circle
Review PySpark functions and Databricks usage.
circle
Practice CI/CD and GitHub workflows.
circle
Revisit machine learning model optimization.
Behavioral Questions
circle
Discuss a challenging project experience.
circle
Explain teamwork in past roles.
circle
Share conflict resolution examples.
circle
Describe independent problem-solving scenarios.