Data Scientist

OneMagnify • Detroit, MI

1d

About The Position

Data Scientists at OneMagnify are positioned at the nexus of client strategy and technical execution. They transform intricate business challenges into actionable models, analyses, and insights that clients can directly utilize for decision-making. This role involves close collaboration with Data Engineering, AI, and other cross-functional teams to conceptualize and implement solutions across the entire analytics spectrum, from data integration and quality assurance to predictive modeling and advanced analytics. It is ideal for individuals seeking to engage in substantial technical work with tangible real-world impact. The work directly influences high-stakes client decisions concerning customers, markets, and products. The models developed, such as demand forecasting, audience segmentation, and spend optimization, form the analytical foundation of client operations. Success in this role means driving measurable outcomes, and accountability is a key aspect. Contributors will also help build the scalable analytics capabilities that OneMagnify offers, necessitating the creation of reproducible, maintainable, and extensible code and documentation. Model deployment is viewed as the starting point, not the conclusion. Daily interactions include cross-functional collaboration with engineering, strategy, and delivery teams, requiring constant translation between technical and business domains. The role offers exposure to diverse industries and problem types (e.g., automotive, retail, financial services), fostering both breadth and depth of experience, with a variety of problems encountered regularly.

Requirements

• BA/BS in Computer Science, Statistics, Mathematics, MIS, Marketing Research, or a related quantitative field — or equivalent practical experience
• 2–5+ years of hands-on analytics including predictive modeling, A/B testing, and optimization
• Advanced SQL and Python; strong ability to query, manipulate, and interpret data from databases and data warehouses
• Hands-on experience with Databricks for large-scale data processing and machine learning workflows
• Proficiency with Tableau and/or Power BI for visualization and reporting
• Experience with Git/GitLab for version control and collaborative development
• Strong Excel and PowerPoint skills
• Proven ability to present analyses to management and collaborate with both business and technical stakeholders
• Experience diagnosing and resolving data-quality issues across multiple platforms
• Understanding of data governance, privacy, and compliance standards

Nice To Haves

• Proficiency with SAS or R in an applied analytics environment
• Familiarity with automotive or VIN data and complex industry-specific data structures
• Exposure to AI-enabled analytics workflows or automation within a data science context
• Experience working in integrated marketing, consulting, or digital services environments where analytics supports client-facing delivery
• Familiarity with Master Data Management (MDM) concepts and how they apply to data quality and integration

Responsibilities

• Build and validate analytical models
• Design, deploy, and monitor models including forecasting, classification, regression, and segmentation
• Conduct A/B testing and causal analyses with rigorous experimental design and clear documentation
• Develop optimization solutions (linear, mixed-integer, multi-objective) and ensure reproducibility across the full model lifecycle
• Own data integration and quality
• Integrate data from multiple sources and develop data-quality reporting that surfaces issues before they become client problems
• Conduct root-cause analysis on data anomalies and validate database changes prior to release
• Use Databricks for large-scale data processing and machine learning workflows
• Translate requirements into technical solutions
• Partner with business and engineering teams to elicit requirements, define business rules, and turn them into technical specifications
• Document solutions clearly enough that someone else can maintain and extend your work
• Ensure alignment between what clients ask for and what gets built
• Communicate findings to varied audiences
• Synthesize and present analytical findings to internal and external stakeholders, including executive-level audiences, with the judgment to handle complex or sensitive inquiries with care
• Build metrics and KPI reports that inform real business decisions, not just dashboards that get ignored
• Prepare visualizations in Tableau and Power BI that make complex outputs accessible
• Support collaborative development
• Use Git/GitLab for version control, reproducibility, and collaborative code development
• Collaborate with engineering teams to implement MLOps practices including model deployment, monitoring, and end-to-end lifecycle management using tools such as MLflow
• Adhere to data governance, privacy, and compliance standards across all work

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Associate degree