Principal Data Scientist

Jobtailor; Dearborn (MO); On-site; USD 150,000 - 190,000; Full time

Job summary

Jobtailor seeks a lead data scientist to design and deploy end-to-end ML models for complex platform data challenges. You will own identity resolution, data quality and scalable data pipelines while partnering with cross-functional teams to deliver impactful analytics.

The role emphasizes mentoring, ML monitoring tools, and advancing data warehousing and cloud-native data services with Python, SQL, and BigQuery. On-site in Dearborn, MO with strong collaboration.

Qualifications

• Ph.D. in Computer Science, Statistics or Mathematics.
• 5+ years in data science or related field.
• 5+ years Python development with Pandas/NumPy/Scikit-learn.
• 5+ years ML frameworks and libraries (e.g., PySpark, BigQuery ML, Pandas, Scipy-Weave, etc.).
• 3+ years SQL experience for complex datasets.

Responsibilities

• Design, build and deploy ML algorithms for platform data challenges.
• Develop identity resolution algorithms and production deployment.
• Identify and resolve data quality issues across data warehouses/lakes.
• Build ML-driven monitoring tools for anomaly detection and data quality checks.
• Mentor data engineers and collaborate with global stakeholders.

Skills

Machine Learning

Python Development

Data Quality

SQL Query Optimization

Mentoring

Project Leadership

Communication

Education

Ph.D. in Computer Science

Ph.D. in Statistics

Ph.D. in Mathematics

Tools

Python

Pandas

NumPy

Scikit-learn

Pyspark

BigQuery

SQL

Docker

Graph ML libraries

NLTK

Job description

• Design, build, and deploy end-to-end machine learning algorithms for complex platform data challenges
• Develop identity resolution algorithms, refine them for accuracy and performance at scale, and support production deployment
• Identify, analyze, and resolve complex data quality issues across large-scale data warehouses and data lakes
• Design and implement ML-driven monitoring tools for anomaly detection, data cleansing, standardization, and validation
• Develop internal tools, libraries, and automation scripts for data lineage, metadata management, and automated data quality checks
• Build and manage Docker images and automate algorithms for orchestration and scheduling
• Apply statistical analysis and predictive modeling to evaluate large-scale data pipelines, ETL/ELT processes, and data storage solutions
• Implement data-driven improvements to optimize data flow, achieve sub-second latency, and improve resource utilization
• Perform root cause analysis on data discrepancies, performance bottlenecks, and system failures
• Drive strategic development of data science capabilities within the Product group and lead R&D efforts
• Leverage Generative AI and LLMs to identify problems and develop solutions in data platform and data warehouse environments
• Partner with data engineers and architects to design, optimize, and maintain scalable data structures and cloud-native data services
• Manage data ingestion from various sources and formats into BigQuery and other data platforms
• Implement transformation processes for downstream analytical consumption
• Act as a key liaison and project leader, mentor data engineers, and collaborate with global stakeholders
• Translate complex business requirements into technical specifications for data solutions
• Serve as a technical conduit between central privacy, product, and engineering teams for end-to-end system design
• Create documentation for data structures, data quality rules, and analytical findings
• Share expertise, mentor junior team members, and foster best practices across the organization

Requirements

• Ph.D. in Computer Science, Statistics, Mathematics or a related field
• 5 years of experience in the job offered or a related occupation
• 5 years of experience in data science or advanced data engineering
• 5 years of experience with Python development, including Pandas, NumPy, and Scikit-learn, for data manipulation, analysis, and scripting
• 5 years of experience using machine learning frameworks and libraries, including at least 5 of: Pyspark, BigQuery ML, Pandas, Scipy-Weave, Multiprocessing, Graph ML libraries, Neo4j, NLTK, or Matplotlib
• 5 years of experience designing, implementing, and deploying machine learning models for complex data problems, including anomaly detection or predictive maintenance, with algorithm fine-tuning for performance and accuracy at scale
• 5 years of experience researching, evaluating, and integrating new ML capabilities
• 3 years of experience using SQL for querying, manipulating, and optimizing complex datasets, including query tuning
• Must be legally authorized to work in the United States
• Must live within a reasonable commuting distance from the Dearborn, Michigan worksite

Core Competencies

Demonstrates expertise in designing and deploying machine learning algorithms, with a strong focus on data quality, anomaly detection, and performance optimization. Proficient in Python and various machine learning frameworks, with a proven ability to mentor teams and collaborate across functions.

Highest-signal resume keywords

• Machine Learning Model Deployment
• Python Development
• Data Quality Management
• Statistical Analysis
• SQL Query Optimization

Hard Skills

• Machine Learning Algorithms
• Data Manipulation
• Predictive Modeling
• Anomaly Detection
• Data Engineering
• ETL Processes
• Data Cleansing
• Statistical Analysis
• Algorithm Fine-Tuning
• Data Lineage

Soft Skills

• Mentoring
• Collaboration
• Project Leadership
• Communication

Certifications & Qualifications

• Ph.D. in Computer Science
• Ph.D. in Statistics
• Ph.D. in Mathematics

Industry Keywords

• Data Science
• Data Engineering
• Data Warehousing
• Cloud-Native Data Services
• Data Quality Rules

Tools & Technologies

• Python
• Pandas
• NumPy
• Scikit-learn
• Pyspark
• BigQuery
• SQL
• Docker
• Graph ML libraries
• NLTK