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.