Trinus Corporation

AI, Data Science & Advanced Analytics

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AI, Data Science & Advanced Analytics Consultant, offering a contract of unspecified length at a pay rate of "unknown". Key skills include SQL, Databricks, and advanced analytics. A bachelor's degree and relevant certifications are required.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
Unknown
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πŸ—“οΈ - Date
April 14, 2026
πŸ•’ - Duration
Unknown
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🏝️ - Location
Unknown
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πŸ“„ - Contract
Unknown
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πŸ”’ - Security
Unknown
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πŸ“ - Location detailed
Alhambra, CA
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🧠 - Skills detailed
#Deployment #NLP (Natural Language Processing) #"ETL (Extract #Transform #Load)" #SQL Server #Programming #Forecasting #Predictive Modeling #Data Quality #Classification #Statistics #Microsoft Azure #Databases #AWS (Amazon Web Services) #Oracle #Visualization #Azure #AI (Artificial Intelligence) #Data Architecture #Data Engineering #Cloud #Data Warehouse #SQL (Structured Query Language) #Clustering #ML (Machine Learning) #Regression #Data Science #Database Design #Data Pipeline #PostgreSQL #Data Transformations #Snowflake #Mathematics #Databricks #AWS Machine Learning #Computer Science #Data Management #Scala #Data Analysis
Role description
Position Description: We are seeking an AI, Data Science & Advanced Analytics Consultant to strengthen data-driven decision-making, improve operational efficiency, and maximize the use of modern data platforms such as Databricks. This role will provide specialized expertise to accelerate program development, support the design and deployment of advanced analytics solutions, and ensure alignment between data, technology, and business goals. The consultant will also play a key role in building foundational capabilities, facilitating knowledge transfer to internal teams, and enabling Public Works to sustainably scale its data science and AI initiatives. Job Responsibilities & Skills: β€’ Exceptional communication and stakeholder engagement skills, with the ability to clearly translate complex data, analytical models, and AI concepts into actionable insights for both technical and non-technical audiences, while maintaining a strong customer service orientation. β€’ Advanced analytical and business acumen, including experience with statistical methods and modeling techniques such as regression analysis, association analysis, clustering, and outlier detection, along with a solid foundation in exploratory data analysis and problem framing. β€’ Working knowledge of data architecture and database design principles, with the ability to collaborate effectively with Data Management and Data Engineering teams to ensure data quality, accessibility, and alignment with enterprise standards. β€’ Proficiency in data visualization and reporting tools to effectively communicate insights, trends, and performance metrics to support decision-making. β€’ Strong project and time management capabilities, with a proven ability to manage multiple priorities, meet deadlines, and deliver high-quality outputs in a fast-paced, evolving environment. β€’ Demonstrated ability to work both collaboratively and independently, driving initiatives forward with minimal oversight while aligning data, analytics, and business objectives across cross-functional teams. β€’ High attention to detail and commitment to data quality, ensuring accuracy, consistency, and reliability in all analyses, models, and deliverables. β€’ Experience supporting the development and operationalization of data science solutions, including contributing to scalable analytics frameworks and enabling knowledge transfer to internal teams. Experience Required: β€’ 6 years of experience in data analysis, analytics, data visualization and reporting with the ability to present insights to business and executive stakeholders. β€’ 6 years of experience with SQL programming, using data sources such as SQL Server, Oracle, PostgreSQL, or similar relational databases. β€’ 3 years of experience working with Databricks, Genie and similar AI cloud-based analytics platforms, including notebook development, feature engineering, Machine Learning model training, and workflow orchestration. β€’ 3 years of experience collaborating with data engineering and data science teams to design data pipelines, optimize data transformations, and implement Lakehouse or data warehouse architectures (e.g., Databricks, Snowflake, SQL-based platforms). β€’ 2 years of experience applying advanced analytics and predictive modeling (e.g., regression, classification, clustering, forecasting, natural language processing). Education Required: β€’ Bachelor’s degree in Data Science, Computer Science, Statistics, Applied Mathematics, Engineering, Information Technology, or a closely related quantitative field. 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 or equivalent advanced analytics certifications.