Senior Data Scientist

Must Haves:

• Strong communication skills - can efficiently communicate with a wide variety of audiences
• Comfortable with pure data science and data engineering
• Delivery/Product/Price optimization experience
• Work on full stack
• Experience with price optimization/elasticity
• Python
• Databricks
• AWS
• Data Sourcing

Ideal candidates will also have:

• Sharing a copy of portfolio/git hub is a plus
• Elasticity model experience is a plus
• Experience with AI - building agents for pricing strategy & pricing optimization
• Experience building data apps, plus

Job Description:

• The Senior Data Scientist plays a critical role in shaping the future of business by developing algorithms and models that forecast trends and translate business needs into actionable analytics for executive decision-making. With a strong foundation in AI/ML and pricing optimization, this role leads ML model experimentation scaling sensitivity-to-elasticity experiments across more markets simultaneously while driving model measurement, tuning, and pilot measurement strategy. By conducting large-scale experiments, the Senior Data Scientist addresses complex business questions and uncovers hidden relationships within extensive datasets.

Duties and Responsibilities

• Perform Exploratory Data Analysis (EDA) and initial investigations on data to discover patterns, spot anomalies, and check assumptions
• Build predictive models using statistical and machine learning techniques, with a focus on pricing optimization and elasticity modeling
• Augment ML model experimentation by scaling sensitivity-to-elasticity analyses, enabling more experiments and markets to run concurrently
• Design and execute pilot measurement strategies to evaluate model performance in live environments before full deployment
• Continuously measure, monitor, tune, and optimize models within the production environment to ensure health, accuracy, and business impact
• Create visual representations of data to communicate findings effectively and share with other Data Scientists for input and storytelling
• Work with cross-functional teams, including engineers, service owners, product owners, product managers, and business stakeholders, to understand data needs and challenges
• Prepare reports and presentations to convey insights and recommendations
• Gather data from various sources and ensure its quality and integrity
• Stay updated with the latest tools, techniques, and industry trends in data science and AI/ML and bring ideas to the table for how to improve the use of data and analytics
• Design and execute comprehensive data analyses using advanced methodologies and statistical modeling to produce insightful reports essential for strategic planning
• Utilize analytical tools and hypothesis-driven analysis to enhance machine learning projects
• Implement cutting-edge AI techniques to boost data analysis efficiency
• Perform data sampling

Minimum Qualifications/Requirements

• Bachelor s degree in mathematics, Statistics, Computer Science, or related field; master's degree preferred
• Typically, 5+ years of relevant quantitative and qualitative research, analytics, data science, or machine learning experience
• Demonstrated experience with pricing optimization models and elasticity analysis
• Experience and solid understanding of machine learning algorithms and relational databases
• Experience with data science modeling, statistics, analytics, business intelligence, or data-driven business strategy
• Proven experience in model measurement, monitoring, and tuning within a production environment
• Experience managing and delivering complex and technical products
• Experience performing statistical analysis and applying visualization techniques
• Native-level proficiency/fluency in English

Preferred Skills

• Knowledge of data models and structures, as well as database design tools and query languages
• Knowledge of multiple programming languages and statistical analysis tools such as Python, C++, JavaScript, R, SAS, Excel, SQL, MATLAB, and SPSS
• Knowledge of statistical and data mining techniques such as generalized linear models (GLM)/regression, random forest, boosting, trees, text mining, hierarchical clustering, deep learning, convolutional neural networks (CNN), and recurrent neural networks (RNN)
• Strong working knowledge of AI/ML techniques with the ability to flex between data science and applied ML roles as business needs evolve
• Experience designing and executing pilot measurement strategies and evaluating experiment results at scale across multiple markets
• Basic knowledge of AI, its potential roles in solving business problems, and the future trajectory of generative AI models
• Demonstrated communication, collaboration, and stakeholder management skills to build strong relationships with IT and the business
• Demonstrated data analysis and data modeling skills to identify patterns, trends, and solutions to complex problems
• Basic technical leadership skills encompassing employee coaching, objective setting, and fostering professional development
• Ability to clearly communicate concepts and present complex data findings to both technical and business executives
• Ability to conduct statistical analyses and build models with advanced scripting languages

Attention to detail and ability to maintain data accuracy and integrity