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Data Scientist - Job Opportunity at Engage3

Scottsdale, AZ, US

Full-time

Mid-level

Posted: June 7, 2025

Remote

Based on the mid-level experience requirement, remote work flexibility, and specialized pricing optimization focus, this role likely offers compensation in the range of $90,000 to $130,000 annually, with potential for equity participation given the specialized nature of the retail technology sector and the strategic importance of pricing optimization capabilities.

Key Responsibilities

Architect and deploy cutting-edge models and algorithms that drive transformative pricing strategies, directly impacting retail industry revenue optimization and competitive positioning

Execute comprehensive end-to-end data analysis workflows that transform raw business data into actionable intelligence, ensuring data integrity and analytical rigor across all pricing solutions

Lead the strategic development and maintenance of optimization pipelines using Python, establishing robust testing frameworks and debugging protocols that ensure scalable, production-ready solutions

Evaluate and optimize deployed solutions through continuous performance monitoring, delivering data-driven insights that adapt to evolving business needs and market conditions

Drive proactive business intelligence initiatives by identifying emerging business questions, conducting advanced exploratory data analysis, and implementing customized solutions that anticipate market opportunities

Collaborate strategically with cross-functional engineering teams to translate complex business requirements into robust, scalable production systems that integrate seamlessly across the technology stack

Partner with application development teams to ensure newly developed analytical features are effectively incorporated into client-facing tools, enhancing user experience and business value delivery

Create comprehensive documentation and knowledge transfer materials that bridge technical methodologies with business stakeholder understanding, ensuring organizational knowledge retention and scalability

Requirements

Education

Advanced degree (M.S. or Ph.D.) in Engineering, Math, Finance, Computer Science, Physics or equivalent industry experience as a project leader

Experience

3+ years of experience in large-scale data analysis and modeling

Required Skills

Strong proficiency in Python, including experience with libraries such as Pandas, NumPy, Scikit-learn Experience writing efficient SQL queries and working with large relational databases Solid understanding of statistical inference, predictive modeling, and data visualization principles Strong communication skills with the ability to explain technical concepts clearly Excellent problem-solving skills and critical thinking; ability to derive actionable insights from complex data Ability to work independently, manage multiple priorities, and thrive in a fast-paced team environment

Sauge AI Market Intelligence

Industry Trends

The retail pricing optimization sector is experiencing unprecedented growth driven by AI and machine learning adoption, with companies increasingly investing in dynamic pricing strategies to maintain competitive advantage in volatile market conditions. This trend is accelerated by the need for real-time price adjustments based on competitor analysis, demand forecasting, and inventory optimization. Price intelligence and competitive analysis platforms are becoming essential infrastructure for retail operations, with the market expected to grow significantly as traditional retailers digitize their pricing strategies to compete with e-commerce giants. This creates substantial demand for data scientists who can build and maintain sophisticated pricing algorithms. The integration of behavioral economics with traditional pricing models is emerging as a key differentiator, requiring data scientists who can analyze consumer psychology alongside market dynamics to optimize price perception and purchase behavior across different customer segments.

Role Significance

The role likely operates within a specialized analytics team of 5-8 professionals, collaborating closely with engineering, product, and business stakeholders. The mention of cross-functional collaboration suggests matrix-style project work with multiple teams while maintaining core reporting within the analytics organization.

This role represents a mid-level individual contributor position with significant technical ownership and cross-functional influence. The responsibilities indicate substantial autonomy in solution design and implementation, with expectations for proactive business problem identification and strategic thinking that extends beyond pure technical execution.

Key Projects

Development of dynamic pricing algorithms that analyze competitor pricing, market conditions, and demand patterns to optimize revenue and market share across product categories Implementation of price elasticity models that predict consumer response to pricing changes, enabling strategic pricing decisions that maximize profitability while maintaining competitive positioning Creation of automated price monitoring and adjustment systems that process large-scale market data in real-time, providing retail clients with competitive intelligence and pricing recommendations

Success Factors

Technical excellence in statistical modeling and machine learning, particularly in optimization algorithms and predictive analytics, combined with the ability to translate complex mathematical concepts into practical business applications that drive measurable revenue impact. Strong business acumen in retail pricing strategy and competitive dynamics, enabling the identification of market opportunities and the development of pricing solutions that align with broader business objectives and market positioning strategies. Exceptional communication and collaboration skills that facilitate effective partnership with diverse stakeholders, from technical engineering teams to business executives, ensuring that analytical insights are properly understood and implemented across the organization. Adaptability and continuous learning mindset in a rapidly evolving technology landscape, with the ability to stay current with emerging trends in AI, machine learning, and retail technology while maintaining deep expertise in pricing optimization methodologies.

Market Demand

High demand exists for data scientists with pricing optimization expertise, as this represents a critical competitive advantage in retail. The combination of statistical modeling skills with business acumen in pricing strategy creates a relatively narrow talent pool, leading to competitive compensation and strong job security in this specialized field.

Important Skills

Critical Skills

Python proficiency with statistical and machine learning libraries represents the core technical foundation for this role, as it enables the development and deployment of sophisticated pricing algorithms and optimization models that form the backbone of the company's analytical capabilities and competitive advantage SQL expertise and database management skills are essential for handling large-scale retail data processing and analysis, enabling the extraction and transformation of complex datasets that fuel pricing optimization models and provide the data foundation for strategic business decisions Statistical inference and predictive modeling knowledge forms the mathematical foundation for developing accurate pricing models and optimization algorithms, directly impacting the quality and reliability of pricing recommendations that drive client revenue and market positioning

Beneficial Skills

Advanced machine learning techniques including ensemble methods, deep learning, and reinforcement learning could provide significant competitive advantages in developing next-generation pricing optimization algorithms that adapt to complex market dynamics and consumer behavior patterns Business intelligence and data visualization expertise using tools like Tableau, Power BI, or advanced Python visualization libraries would enhance the ability to communicate complex analytical insights to business stakeholders and facilitate data-driven decision making across the organization Cloud computing platforms and distributed computing frameworks such as AWS, Azure, or Apache Spark would enable the development of more scalable and efficient data processing pipelines, supporting the analysis of increasingly large and complex retail datasets

Unique Aspects

The role offers direct exposure to transformative retail industry innovation, providing opportunities to build solutions that have immediate, measurable impact on major retail operations and pricing strategies across multiple market segments

Combination of advanced statistical modeling with practical business application in a high-stakes environment where pricing decisions directly impact revenue and competitive positioning, offering unique learning opportunities in applied data science

Remote work flexibility paired with specialized domain expertise in pricing optimization creates an attractive career positioning that combines lifestyle benefits with deep technical specialization in a high-demand field

Opportunity to work across the full data science lifecycle from research and development through production deployment and performance optimization, providing comprehensive experience in scalable data science solution delivery

Career Growth

Career progression typically occurs over 2-4 years for advancement to senior individual contributor roles, with management track opportunities emerging after 4-6 years of demonstrated technical leadership and business impact. The specialized nature of pricing optimization expertise can accelerate progression due to high market demand.

Potential Next Roles

Senior Data Scientist or Lead Data Scientist roles with expanded team leadership responsibilities and ownership of larger, more complex pricing optimization initiatives across multiple business units or client segments Principal Data Scientist or Data Science Manager positions that combine deep technical expertise with people management responsibilities, overseeing teams of data scientists and setting technical strategy for pricing analytics capabilities Director of Analytics or Head of Data Science roles that focus on organizational leadership, strategic planning, and cross-functional partnership with executive teams to drive data-driven decision making across the entire business

Company Overview

Engage3

Engage3 operates as a specialized technology provider in the retail pricing intelligence and optimization space, focusing on delivering sophisticated analytical tools and insights that help retailers optimize their pricing strategies and competitive positioning. The company appears to maintain a strong focus on innovation in price management solutions, leveraging advanced data science and machine learning capabilities to serve retail clients.

As a focused player in the pricing optimization sector, Engage3 likely holds a strong position within its niche market, competing with both established enterprise software providers and emerging analytics-focused startups. The company's emphasis on next-generation transformative solutions suggests a growth-oriented market position with significant investment in research and development.

The Scottsdale, Arizona location combined with remote work flexibility suggests a strategic positioning that balances access to Southwest technology talent with national market reach. This location choice often indicates a focus on operational efficiency while maintaining proximity to major retail markets and technology centers.

The emphasis on cross-functional collaboration, independent work, and fast-paced environment suggests a dynamic, results-oriented culture that values innovation and technical excellence. The remote work option and focus on cutting-edge technology indicates a modern, flexible workplace that prioritizes outcomes over traditional corporate structures.

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Data Scientist - Job Opportunity at Engage3

Key Responsibilities

Requirements

Education

Experience

Required Skills

Sauge AI Market Intelligence

Industry Trends

Role Significance

Key Projects

Success Factors

Market Demand

Important Skills

Critical Skills

Beneficial Skills

Unique Aspects

Career Growth

Potential Next Roles

Company Overview

Engage3

Data Sources & Analysis Information

Job Listings Data

Sauge AI Market Intelligence