Sr Data Scientist

• Data Analysis & Modeling: Design and develop complex predictive and prescriptive models using advanced statistical and machine learning techniques. Utilizing data-science techniques, explore the data to uncover patterns and correlations, predict customer behavior, and preemptively identify potential problems. Contribute to company A/B testing framework and recommend results
• Data Collection & Management: Lead the acquisition, integration, and cleaning of diverse and complex datasets from multiple sources to ensure data quality and reliability
• Data Product Ownership: Drive end-to-end data science products from ideation to production, including problem definition, data exploration, model development, and result validation, documentation, and monitoring.
• Collaboration: Work closely with stakeholders across business units, including product, finance, marketing, operations, and IT, to understand business needs, define requirements, and align data science solutions with business objectives.
• Data Visualization & Communication: Create compelling visualizations and presentations that effectively communicate complex analysis, insights, and recommendations to both technical and non-technical audiences.
• Model Deployment & Scaling: Implement and optimize machine learning models in production environments, ensuring they are scalable, efficient, and reliable
• Mentorship & Leadership: Lead by example to build a culture of accountability and rigor to substantiate proven business impact with data, providing mentorship and guidance to other analysts on the team
• Innovation: Keep current with technical and industry developments, tools, and technologies in the field of data science, and identify opportunities for continuous improvement and innovation within the organization

• Data Analysis & Modeling: Design and develop complex predictive and prescriptive models using advanced statistical and machine learning techniques. Utilizing data-science techniques, explore the data to uncover patterns and correlations, predict customer behavior, and preemptively identify potential problems. Contribute to company A/B testing framework and recommend results
• Data Collection & Management: Lead the acquisition, integration, and cleaning of diverse and complex datasets from multiple sources to ensure data quality and reliability
• Data Product Ownership: Drive end-to-end data science products from ideation to production, including problem definition, data exploration, model development, and result validation, documentation, and monitoring.
• Collaboration: Work closely with stakeholders across business units, including product, finance, marketing, operations, and IT, to understand business needs, define requirements, and align data science solutions with business objectives.
• Data Visualization & Communication: Create compelling visualizations and presentations that effectively communicate complex analysis, insights, and recommendations to both technical and non-technical audiences.
• Model Deployment & Scaling: Implement and optimize machine learning models in production environments, ensuring they are scalable, efficient, and reliable
• Mentorship & Leadership: Lead by example to build a culture of accountability and rigor to substantiate proven business impact with data, providing mentorship and guidance to other analysts on the team
• Innovation: Keep current with technical and industry developments, tools, and technologies in the field of data science, and identify opportunities for continuous improvement and innovation within the organization

#LI-AR2

• 4+ Years in data analytics, business intelligence, or data engineering. Data Science Experience preferred
• 2 years in a senior analyst capacity, preferably within an enterprise or large-scale organization
• Experience with retail analytics + omnichannel will be a plus

• Ability to work well under pressure while consistently meeting time-sensitive deadlines
• Ability to work well independently, as well as effectively contribute to a team environment
• Ability to prioritize workload, meet multiple deadlines simultaneously in a fast-paced, frequently changing environment
• Strong interpersonal, written, and verbal communication skills, detail-oriented, with the ability to interact with all levels of end users and technical resources
• Proficiency in programming languages such as Python, R, or Scala
• Expertise in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-Learn). Preference toward experience in a cloud enterprise environment, such as Google Cloud Platform (Google Cloud Platform) (BigQuery is a plus) / Azure / Amazon Web Services (AWS)
• Advanced knowledge of SQL and experience with relational and non-relational databases, with a focus on transforming data
• to prepare for analysis and machine learning. 3+ years of experience in enterprise-grade data visualization tools (e.g., Tableau, Power BI, Looker, MicroStrategy)
• Strong Microsoft Office program experience, including Excel, Word, and PowerPoint.

Equal Opportunity Employer: Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status.

At Randstad Digital, we welcome people of all abilities and want to ensure that our hiring and interview process meets the needs of all applicants. If you require a reasonable accommodation to make your application or interview experience a great one, please contact

Pay offered to a successful candidate will be based on several factors including the candidate's education, work experience, work location, specific job duties, certifications, etc. In addition, Randstad Digital offers a comprehensive benefits package, including: medical, prescription, dental, vision, AD&D, and life insurance offerings, short-term disability, and a 401K plan (all benefits are based on eligibility).

This posting is open for thirty (30) days.