US Data Scientist - Advanced Analytics

Job Title: US Data Scientist - Advanced Analytics
Job ID: 26-21149
Location: Onsite, Dallas, TX
Duration: 12 Months

Required skills:


This is a Dallas/TX Onsite position. Mandatory 3 to 5 days work from office8+ years of Administration experience in multiple complex applications and tools • Software Configuration Management expertise • Experience administering GitLab, Artifactory, Xray, & SonarQube • Experience with Terraform and Ansible • Understanding and working knowledge of containerization on Kubernetes/Open Shift • Familiarity with cloud platforms such as AWS, Azure, and *** Cloud • Strong communication skills and a track record of cross-team collaboration • Working knowledge of different Software Development Lifecycle Methodologies • Experience configuring and managing GitLab Runners, Groups, Projects, and Permissions at scale *CONTINUE IN COMMENTS*

Nice to have skills:

A BS in Computer Science or equivalent work experience with good scripting/programming skills • GitLab Certified Administrator • Recent experience administering GitLab Self-Managed • Prior software experience with build management, configuration management and/or quality testing • Experience with SCM practices including Agile, continuous integration (CI) and continuous deployment


A Data Scientist with Advanced Analytics skills is a professional who leverages deep data and analytics expertise with strong business acumen to address business challenges. They utilize data preparation, analysis, and predictive modeling to forecast trends and suggest optimizations for improved business outcomes. The role requires proficiency in mathematical optimization, discrete-event simulation, rules programming, and predictive analytics. Key technologies include . This comprehensive skill set enables Data Scientists to effectively manage and analyze diverse data types and structures, ensuring data-driven decision-making and business optimization. Key skills encompasses proficiency in programming languages, particularly Python, and the use of development environments like PyCharm, VS Code, and Jupyter Notebooks. It includes expertise in data manipulation using tools such as Pandas, NumPy, and Dask, and data visualization with Matplotlib, Seaborn, and Plotly. Scripting abilities in shell scripting, along with experience in managing databases like SQL, MongoDB, Cassandra, PostgreSQL, and MySQL, are also included. Additionally, the skill set features knowledge of version control systems such as Git, GitHub, and GitLab, and continuous integration and deployment (CI/CD) tools like Docker, Podman, and Jenkins. Optimization skills are highlighted with tools like *** CPLEX and Gurobi, and statistical analysis capabilities are demonstrated with SPSS, SAS, R, and Python. The professional is also familiar with machine learning, statistical modeling, and custom models in applications like supply chain management, pricing, risk assessment, and fraud detection

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