Data Scientist I

Description

This position is considered hybrid for candidates living in the Rochester, NY area.  

Butler/Till is a results-driven marketing agency offering deeply collaborative client experiences, proprietary technology, and world-class partnerships.  At Butler/Till, we take immense pride in our independent, women-owned and led status, our unwavering commitment to a purpose-driven approach, our B-Corp status, and our unique structure as a 100% employee-owned company (ESOP). 

SUMMARY   

Solve complex business problems by integrating and analyzing large datasets from diverse sources, including third-party platforms and relational databases (both structured and unstructured). Utilize data mining, visualization, predictive, prescriptive, and mathematical optimization techniques to identify actionable insights. Mentor and train Campaign Analytics teams, assist with training and the delivery of complex client deliverables. 

KEY OUTCOMES & RESPONSIBILITIES  

Key Outcome: Understand business problems and translate into translate into Data Requirements. 

Key Responsibilities:  

• Engage with Marketing Science senior team, Account Management, Channel Activation, and Integrated Planning teams to define business problems to be solved with data science.  
• Work with senior members of the team to determine the appropriate methodology, and mix of data transformation and analytic tools, to solve business challenges.  
• Learn to build and deliver advanced analytic products and solutions for our clients including clustering/segmentation, marketing and media mix modeling, and optimization, ROI/RoAS forecasting using regression modeling, random forest, machine learning and other techniques. 

Key Outcome: Assist in the development of Marketing Science products and services. 

Key Responsibilities:  

• Collaborate with Data Engineering and/or Software Development teams to understand, plan out and conduct complex data transformations in support of predictive/prescriptive analytics products and services, specialty dashboards and reports that leverage Data Science.  
• Assist in the creation of training materials for the Account Management and Integrated Planning teams as new Marketing Science products and services are developed and launched. 
• Work with senior members of the team to help stakeholders and clients understand the principles and the math behind the analytic methodologies used to build out our products and services.  

Key Outcome: Construct client deliverables 

Key Responsibilities:   

• Assist in the creation of PowerPoint slides to articulate methodology and techniques, with most of the content focused on insights and client business value gleaned from the Marketing Science product or service. 
• Collaborate with senior members of the Marketing Science team, Account Management, Channel Activation, and Integrated Planning teams to provide actionable insights from deliverables including clustering/segmentation, predictive models, and prescriptive analytic solutions. 
• Assist in the presentation of information using data visualization techniques.  
• Collaborate with Data engineering team to understand and plan out the implementation of scoring and other algorithms in production environments using SQL, Python, or other languages.  

Other Responsibilities:

With leadership assistance as needed, hone the ability to define problems, collect and review data, identify and evaluate data patterns and validate statistical assumptions, establish facts, draw valid conclusions, package insights, and present actionable business recommendations.  

Requirements

REQUIRED QUALIFICATIONS  

• Requires a bachelor’s degree in computer science, Data Science, Mathematics, Statistics, or a related field.  
• 2+ years of relevant analytics experience in exploratory data analysis, predictive modeling techniques, and clustering. 
• Familiarity with Media Mix Modeling 
• Extensive use of relational databases including Access, Oracle, SQL Server  
• Experience working in cloud environments such as AWS, Snowflake, and Azure. 
• Intermediate technical and programming skills in SQL and Python (or R studio) and other statistical or machine learning tools with an eagerness to become expert 
• Intermediate knowledge of statistical modeling and machine learning techniques such as linear and logistic regression, decision trees, neural networks, random forest, k-means cluster analysis, time series analysis and forecasting 
• Experience in forecasting/predictive analytics, quantitative analytics, statistical analysi