Job Details

Job Description:

• Create and Implement complex models and algorithms as instructed to drive analytical solutions throughout the organization.
• Conduct advanced statistical and visualize exploratory analysis as instructed to provide actionable insights, identify trends, and measure performance.
• Utilize modern cloud technologies and employ best practices from DevOps/MLOps to produce enterprise-quality production Python and SQL code as part of an agile team.
• ctively participate in problem-solving to enrich possible solutions and flexibly seek out new work or training opportunities to broaden experience.
• Collaborate with the agile team to communicate the design, functioning, and output of models, analysis, and solutions developed.
• Performs other duties as required.

Qualifications:

Minimum Requirements:

• Bachelors degree in a technical engineering or analytical field (Statistics, Mathematics, etc.) or related discipline and one (1) year of relevant work experience.
• Bachelors degree in a technical engineering or analytical field (Statistics, Mathematics, etc.) or related discipline and one (1) internship in Data Analytics, Data Science, or an analytics-related field that included data analysis as part of the internship.
• Masters degree in a technical engineering or analytical field (Statistics, Mathematics, etc.) or related discipline.
• Python and SQL Programming Experience.
• bility to articulate theoretical concepts in at least one of the following analytical areas.
• Statistics & Statistical Modeling, including Time-Series Modeling.
• Simulation Techniques, including MCMC or an equivalent.
• Neural Networks / Deep Learning.
• Tree Based Machine Learning Algorithms.
• Unsupervised Learning.
• Classification techniques, including Support Vector Machines or an equivalent
• Optimization Heuristics.
• Text Analytics.
• bility to visualize data utilizing programmatic techniques.
• Working knowledge of the Data Science development workflow including data manipulation and cleaning, feature engineering, model selection, model training, model validation, model deployment .

Preferred Qualifications:

• Working Knowledge of MLOps/DevOps concepts (Version Control, CI/CD, Trunk Based Development/PR Based Development/GIT, Test-driven development)
• Working Knowledge of Azure Machine Learning Environment.
• Working Knowledge of Software Engineering and Object Orient Programming Principles.
• Working Knowledge of Distributed Parallel Processing Environments such as Spark or Snowflake.
• Working Knowledge of Edge Analytics, embedded systems, or computer vision.
• Working Knowledge of Data Architecture, engineering, and ETL teams.
• Working knowledge of problem-solving/root cause analysis on Production workloads
• Working Knowledge of Agile, Scrum, and Kanban.
• Confident and experienced in public speaking to large audiences and storytelling with data.