

JRD Systems
Principal Data Scientist
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Principal Data Scientist with a contract length of "unknown" and a pay rate of "unknown." Candidates must have a Master's degree, 5+ years of data science experience, expertise in Databricks, and relevant certifications. Hybrid work location.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
Unknown
-
ποΈ - Date
December 3, 2025
π - Duration
Unknown
-
ποΈ - Location
Hybrid
-
π - Contract
Unknown
-
π - Security
Unknown
-
π - Location detailed
Alhambra, CA
-
π§ - Skills detailed
#Data Engineering #SQL Server #"ETL (Extract #Transform #Load)" #PostgreSQL #Programming #Azure #Clustering #Data Transformations #Databricks #Database Design #Computer Science #Predictive Modeling #Data Pipeline #Regression #Data Science #Python #ML (Machine Learning) #Code Reviews #Data Warehouse #MLflow #NLP (Natural Language Processing) #Forecasting #AWS Machine Learning #Data Management #AWS (Amazon Web Services) #Security #SQL (Structured Query Language) #Classification #Statistics #Compliance #Data Analysis #Oracle #AI (Artificial Intelligence) #Microsoft Azure #Monitoring #Databases #Cloud #Snowflake
Role description
Job description:
β’ The Principal Data Scientist works to establish a comprehensive Data Science Program to advance data-driven decision-making, streamline operations, and fully leverage modern platforms including Databricks, or similar, to meet increasing demand for predictive analytics and AI solutions. The Principal Data Scientist will guide program development, provide training and mentorship to junior members of the team, accelerate adoption of advanced analytics, and build internal capacity through structured mentorship. The Principal Data Scientist will possess exceptional communication abilities, both verbal and written, with a strong customer service mindset and the ability to translate complex concepts into clear, actionable insights; strong analytical and business acumen, including foundational experience with regression, association analysis, outlier detection, and core data analysis principles; working knowledge of database design and organization, with the ability to partner effectively with Data Management and Da
β’ β’ Five (5)+ years of professional experience leading data science initiatives, including developing machine learning models, statistical analyses, and end-to-end data science workflows in production environments.
β’ Three (3)+ years of experience working with Databricks and similar cloud-based analytics platforms, including notebook development, feature engineering, ML model training, and workflow orchestration.
β’ Three (3)+ years of experience applying advanced analytics and predictive modeling (e.g., regression, classification, clustering, forecasting, natural language processing).
β’ Two (2)+ years of experience implementing MLOps practices, such as model versioning, CI/CD for ML, MLflow, automated pipelines, and model performance monitoring.
β’ Two (2)+ years of experience collaborating with data engineering teams to design data pipelines, optimize data transformations, and implement Lakehouse or data warehouse architectures (e.g., Databricks, Snowflake, SQL-based platforms).
β’ Two (2)+ years of experience mentoring or supervising junior data scientists or analysts, including code reviews, training, and structured skill development.
β’ Two (2)+ years of experience with Python and SQL programming, using data sources such as SQL Server, Oracle, PostgreSQL, or similar relational databases.
β’ One (1)+ year of experience operationalizing analytics within enterprise governance frameworks, partnering with Data Management, Security, and IT to ensure compliance, reproducibility, and best practices.
β’ This classification requires possession of a Masterβs degree or higher in Data Science, Statistics, Computer Science, or a closely related field. Additional qualifying professional experience may be substituted for the required education on a year-for-year basis. At least one of the following industry-recognized certifications in data science or cloud analytics, such as:
β’ Microsoft Azure Data Scientist Associate (DP-100)
β’ Databricks Certified Data Scientist or Machine Learning Professional
β’ AWS Machine Learning Specialty
β’ Google Professional Data Engineer
β’ or equivalent advanced analytics certifications. The certification is required and may not be substituted with additional experience.
β’ California Resident Candidates Only. This position is HYBRID (2 days onsite, 2 days telework). Interviews will be conducted via Microsoft Teams. The work schedule follows a 4/40 (10-hour days, MondayβThursday), with the specific shift determined by the program manager. Shifts may range between 7:15 a.m. and 6:00 p.m.
Job description:
β’ The Principal Data Scientist works to establish a comprehensive Data Science Program to advance data-driven decision-making, streamline operations, and fully leverage modern platforms including Databricks, or similar, to meet increasing demand for predictive analytics and AI solutions. The Principal Data Scientist will guide program development, provide training and mentorship to junior members of the team, accelerate adoption of advanced analytics, and build internal capacity through structured mentorship. The Principal Data Scientist will possess exceptional communication abilities, both verbal and written, with a strong customer service mindset and the ability to translate complex concepts into clear, actionable insights; strong analytical and business acumen, including foundational experience with regression, association analysis, outlier detection, and core data analysis principles; working knowledge of database design and organization, with the ability to partner effectively with Data Management and Da
β’ β’ Five (5)+ years of professional experience leading data science initiatives, including developing machine learning models, statistical analyses, and end-to-end data science workflows in production environments.
β’ Three (3)+ years of experience working with Databricks and similar cloud-based analytics platforms, including notebook development, feature engineering, ML model training, and workflow orchestration.
β’ Three (3)+ years of experience applying advanced analytics and predictive modeling (e.g., regression, classification, clustering, forecasting, natural language processing).
β’ Two (2)+ years of experience implementing MLOps practices, such as model versioning, CI/CD for ML, MLflow, automated pipelines, and model performance monitoring.
β’ Two (2)+ years of experience collaborating with data engineering teams to design data pipelines, optimize data transformations, and implement Lakehouse or data warehouse architectures (e.g., Databricks, Snowflake, SQL-based platforms).
β’ Two (2)+ years of experience mentoring or supervising junior data scientists or analysts, including code reviews, training, and structured skill development.
β’ Two (2)+ years of experience with Python and SQL programming, using data sources such as SQL Server, Oracle, PostgreSQL, or similar relational databases.
β’ One (1)+ year of experience operationalizing analytics within enterprise governance frameworks, partnering with Data Management, Security, and IT to ensure compliance, reproducibility, and best practices.
β’ This classification requires possession of a Masterβs degree or higher in Data Science, Statistics, Computer Science, or a closely related field. Additional qualifying professional experience may be substituted for the required education on a year-for-year basis. At least one of the following industry-recognized certifications in data science or cloud analytics, such as:
β’ Microsoft Azure Data Scientist Associate (DP-100)
β’ Databricks Certified Data Scientist or Machine Learning Professional
β’ AWS Machine Learning Specialty
β’ Google Professional Data Engineer
β’ or equivalent advanced analytics certifications. The certification is required and may not be substituted with additional experience.
β’ California Resident Candidates Only. This position is HYBRID (2 days onsite, 2 days telework). Interviews will be conducted via Microsoft Teams. The work schedule follows a 4/40 (10-hour days, MondayβThursday), with the specific shift determined by the program manager. Shifts may range between 7:15 a.m. and 6:00 p.m.





