Analytics Engineer II
Tasks
- Apply machine learning best practices
- Apply statistical analysis methodologies
- Build data engineering tools
- Communicate insights with visualizations
- Conduct exploratory data analysis
- Create reports and presentations
- Define project objectives
- Deploy machine learning solutions
- Design data science pipelines
- Develop clustering models
- Develop predictive models
- Develop regression models
- Develop time-series forecasting models
- Ensure data availability quality and reliability
- Explore structured and unstructured data
- Formulate data-driven hypotheses
- Gather and preprocess data
- Identify KPIs
- Implement MLOps best practices
- Maintain data pipelines
- Mentor junior data scientists
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | AWS | Azure | B testing | Clustering | Data Analysis | Experimental Design | Exploratory Data Analysis | Git | Hadoop | Hypothesis Testing | MLOps | Machine Learning | Matplotlib | NoSQL | Power BI | Predictive Modeling | Python | R | Regression | SQL | Seaborn | Spark | Tableau | Time Series
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
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