Sr Manager Advanced Analytics/Data Science - Randstad USA

job summary:

• Minimum 8 years of experience in the field of data analytics with at least 4 years in a Managerial role. Experience in retail is most desirable.
  
  
• Excellent communication skills, detail-oriented, with the ability to interact with all levels of end users (IC to VP) and technical resources.
  
  
• Hands-on capabilities in developing dashboards, automating data processes, validating data integrity, and building scalable analytical solutions, preferably in an ecommerce or retail setting.
  
  
• Ability to drive innovation and stay current with emerging technologies related to advanced analytics.
  
  
• Technical Skills:
  
  
  • High proficiency in using programming languages like Python, SQL, and BI tools like Tableau/Power BI, Looker, MicroStrategy
    
    
  • Proficient in using any one of the cloud technologies - GCP, AWS, or Azure. GCP hands-on is preferred.
    
    
  • Hands-on expertise with machine learning frameworks and familiarity with LLMs.
• Advanced Analytics:
  
  
  • Data modeling experience in retail or ecommerce will be ideal.
    
    
  • High proficiency in advanced analytics techniques, exploratory data analysis (e.g., linear/logistic regression, cluster analysis), and its application in the right use cases to drive results.
    
    
  • Ideate, build, and test minimum viable products (MVP) and scale data products utilizing state-of-the-art AI technologies.
    
    
  • Experience in building, articulating, and delivering business cases and roadmaps around data use and/or a data-centric business strategy.
    
    
  • Demonstrated management capabilities to handle complex analytical projects from ideation to completion with actionable insights.
• Embrace agile ways of working. Ability to prioritize workload, and meet multiple deadlines simultaneously in a fast-paced, frequently changing environment.
  
  
• Able to work well independently, as well as effectively contribute to mentor, coach, and build highly talented team.
  
  
• Proven to think strategically and translate business objectives into data and analytics strategies and deliver timely results.

 
location: Katy, Texas
job type: Permanent
salary: $150,000 - 155,000 per year
work hours: 8am to 5pm
education: Bachelors
 
responsibilities:

• Mentor the talented team of analysts, data scientists, product managers, and engineers to generate eloquent insights from data to drive the actions and manage the team dynamics. Lead by example to build a culture of accountability and rigor to substantiate proven business impact with data.
  
  
• Provide near-term strategic and tactical plans to execute analytics for the omnichannel team.
  
  
• Collect data, analyze trends, draw conclusions, and provide recommendations on cross-channel marketing tactics and strategies (including broadcast, social media, mobile marketing, and banner ads).
  
  
• Develop and own data products roadmap, ideate and prioritize the requirements and feature engineering for the AI/ML product, and maintain the product backlog.
  
  
• Formulate the work of the Data Science function into findings for application by the broader business, including for use in strategic decision-making and planning.
  
  
• Oversee and contribute to the development and integration of machine learning models for predictive and prescriptive solutions.
  
  
• Open to research and co-create MVP solutions using LLMs from leading AI vendors and share learnings with data Product and Engineering teams.
  
  
• Creates experimental designs (test vs. control) for marketing tactics which allows for accurate ROI measurement.
  
  
• Partner with enterprise engineering and BI teams to evaluate and integrate new data sources and scalable platforms required for the data products while continuously improving data governance and documentation across.
  
  
• Partner with enterprise engineering and BI teams to construct downstream impact analysis and own change management communication for data sources.
  
  
• Define, create, improve, govern, and own metrics documentation that is required to support the data-driven culture of Omnichannel organization.
  
  
• Required to learn company policies, procedures, and safety