Expertise in R, Python, SAS, SQL, Databricks, Snowflake, disparate data sets, data mining, data visualization tools. Tool/Data Utilization expectations (Not limited to): SQL, Vertica, Data Bricks, Python, Data Lakes, PowerBI, Tableau, Snowflake, and other open-sourced programs.

Under the guidance of Clinical Data Sciences, the Clinical Data Engineer provides leadership and guidance at the enterprise level for end-to-end data extraction, transformations and construct of data pipelines that conform to the common data model that ensures data ingestion for all clinical data capture technologies and other related vendor and/or applications (e.g., EDC, IRT, ePRO, eCOA) as well other data models that may be required by end users.

Experience with Databricks, Snowflake, ADLS, Python, SQL, Spark, H2o, model selection/creation, hyperparameter tooling, model interpretation & retraining. Transforming existing code base to Python/SQL Databricks solution with continued maintenance.

The Data Analyst will be part of the Department of Family and Protective Services (DFPS) Office of Data and Systems Improvement (DSI). Additionally, applicants who do not meet the degree requirements may be considered if they display knowledge/skill with R, SQL, Excel, and/or Python, evidenced by sharable code from multiple projects.

Onboard datasets using Airflow, explore data, and automate tasks using a modern Python data stack. Vendor Technical Specialist: Work closely with financial and alternative data vendors to acquire data and solve issues, including Bloomberg, Refinitiv, and many others.

6+ years of experience in SQL, data transformations, statistical analysis, and troubleshooting across more than one Database Platform (Cassandra, MySQL, Snowflake, PostgreSQL, Redshift, Azure SQL Warehouse, etc.

Additionally, the team will continue to steward our custom applications, are built against Oracle and ADABAS data stores, Python/Django or Natural backends, and various front-end frameworks including React, Angular, and Python/Django.

Previous experience with MySQL, Python, R, JMP, Minitab, Tableau, and Ignition, PLC, Robotics. Lead the team to develop and enable data driven operational and financial decisions through predictive insights into tool and process performance, including integration of factory data systems and use of software such as MySQL, Python, R, JMP, Tableau and Ignition.

This high performing team works with clients to implement the full spectrum of data analytics and data science, from data querying and data wrangling, to data visualization and dashboarding, to predictive analytics, machine learning, and artificial intelligence as well as robotic process automation (RPA.

DevOps, DevSecOps, Kubernetes, Docker, Helm, IaC, AWS, Google Cloud, GCP, Bash, Terraform, CI, CD, GitOps, Python, React. + Solid background in Linux, Docker, and automation scripting in one or more of the following languages/tools: Bash, Terraform, Python (AWS CDK, boto) - terraform preferred.

Experience in some of the machine learning areas: Anomaly detection and signal processing, time-series data analysis and modeling, Conventional Machine Learning methods, Computer Vision, Deep learning, CNNsBachelor of Science in Computer Science, Statistics, Mechanical engineering, or other STEM areas.

Or Econometrics, and relevant follow-up graduate studies, such as: Master of Computational Data Science, Master of Science in Machine Learning, Master of Science in Cognitive Science, Master of Science in Artificial Intelligence, Master of Science in Computer Science with AI Specialization, or other related quantitative discipline with a strong foundation in statistics.

Previous experience with one or more modern CI/CD solutions inclusive of Azure DevOps, Github and Bitbucket along with one or more modern advanced analytics tools for machine learning / AI solutions for example, Spark, DataBricks, Python and R; experience with one or more modern advanced business intelligence & visualization solutions (such as PowerBI, Tableau, amongst others) a plus.

Preferred knowledge on ASML NXT or XT platform scanner equipment Proficient data analysis skills and analysis software familiarity (JMP, TIBCO Spotfire, Tableau, MATLAB, other) Python scripting for data analysis is a plus.

Contribute to an optimal data pipeline architecture (SQL, Python, Snowflake, dbt, Airflow, AWS), from multiple raw sources of data to polished datasets for analytic and dashboard consumption.