Sr. Data Scientist – Pricing

Position Overview: The primary responsibility of this role is to design, implement, drive adoption, and measure the impact of innovative analytic solutions while continuously improving existing systems.

Key Analytic Responsibilities:

• Develop predictive models to analyze pricing data and forecast trends.

• Utilize machine learning algorithms to optimize pricing structures.

• Lead the creation of statistical simulation frameworks for decision-making.

• Build time series models using techniques such as Sarima, Prophet, Holt-Winters, and Transformers.

• Guide the implementation of model variance analysis and impact tracking frameworks.

• Lead the deployment of statistical models in production environments.

• Drive the development of simulation-based decision frameworks.

Additional Responsibilities:

• Collaborate with stakeholders to identify analytic needs, gather user requirements, and support model adoption.

• Explore new business development opportunities and assist in maintaining strong, long-term relationships with key stakeholders.

Minimum Requirements:

• Experience: At least 5 years of experience in data science, analytics, or programming, gained through both academic and industry experience.

• Education: A bachelor’s degree in a technical field such as Computer Science, Statistics, Applied Mathematics, Finance, Economics, or related quantitative fields. A Master’s or Ph.D. is preferred.

Critical Skills:

• Proven ability to solve complex problems across the entire data stack, from data wrangling (using SQL or other methods) to large-scale stakeholder consumption.

• Expertise in machine learning and data science best practices.

• Proficiency in statistical programming languages (Python, R).

• Ability to communicate technical concepts effectively to non-technical audiences.

• Experience in object-oriented programming (Python, Java, C#, VBA, etc.).

• Strong understanding of core statistical concepts such as linear regression, A/B testing, outlier analysis, probability distributions, and tests for independence.

Additional Knowledge & Skills:

• Analytical thinking and process-oriented mindset.

• Strong team collaboration skills.

• Excellent verbal and written communication.

• Knowledge of relational databases (e.g., MS SQL Server, Snowflake, Oracle).

• Familiarity with cloud computing platforms (e.g., Azure, AWS, Google Cloud, Databricks) is a plus.

• Proficiency in Excel, financial modeling, and reporting.

• Experience with data mining using enterprise systems (e.g., SAP or JD Edward.