Data Scientist-Advanced Analytics

As a Data Scientist with Advanced Analytics skills, you will leverage deep data and analytics expertise with strong business acumen to address business challenges. You will utilize data preparation, analysis, and predictive modeling to forecast trends and suggest optimizations for improved business outcomes. Your primary responsibilities will include:

• Develop Predictive Models: Design and implement predictive models using mathematical optimization, discrete-event simulation, and rules programming to drive business optimization. This includes utilizing tools like IBM CPLEX and Gurobi for optimization and SPSS, SAS, R, and Python for statistical analysis.
• Analyze Diverse Data: Manage and analyze diverse data types and structures using programming languages like Python and development environments such as PyCharm, VS Code, and Jupyter Notebooks. This involves data manipulation with Pandas, NumPy, and Dask, and data visualization with Matplotlib, Seaborn, and Plotly.
• Deliver Data-Driven Insights: Utilize data preparation, analysis, and predictive modeling to forecast trends and suggest optimizations for improved business outcomes. This includes applying machine learning, statistical modeling, and custom models in applications like supply chain management, pricing, risk assessment, and fraud detection.
• Collaborate on Solution Delivery: Work collaboratively to deliver data-driven solutions, ensuring effective data management and analysis to inform business decision-making.
• Maintain Technical Expertise: Stay up-to-date with industry-leading tools and technologies, including version control systems like Git, GitHub, and GitLab, and continuous integration and deployment (CI/CD) tools like Docker, Podman, and Jenkins.

Master's Degree

Required Technical And Professional Expertise

• Data Analysis and Modeling: Experience with data preparation, analysis, and predictive modeling using tools like Pandas, NumPy, Dask, Matplotlib, Seaborn, and Plotly, with the ability to forecast trends and suggest optimizations for improved business outcomes.
• Programming Languages: Proficiency in programming languages, particularly Python, and experience with development environments like PyCharm, VS Code, and Jupyter Notebooks.
• Data Management: Experience managing and analyzing diverse data types and structures, including databases like SQL, MongoDB, Cassandra, PostgreSQL, and MySQL.
• Optimization and Statistical Analysis: Experience with mathematical optimization tools like IBM CPLEX and Gurobi, and statistical analysis capabilities using SPSS, SAS, R, and Python.
• Technical Tools and Systems: Experience with version control systems like Git, GitHub, and GitLab, and continuous integration and deployment (CI/CD) tools like Docker, Podman, and Jenkins.

Preferred Technical And Professional Experience

• Machine Learning Knowledge: Experience with machine learning, statistical modeling, and custom models in applications like supply chain management, pricing, risk assessment, and fraud detection.
• Scripting Abilities: Shell scripting abilities, along with experience in managing databases like SQL, MongoDB, Cassandra, PostgreSQL, and MySQL.
• Optimization Skills: Experience with tools like IBM CPLEX and Gurobi for optimization.