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Mid-Level Data Scientist
IEBT Innovation. Explore, clean, and analyze large volumes of structured and unstructured data to identify patterns, anomalies, and opportunities .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in analyzing large datasets and developing Machine Learning models, with strong proficiency in Python and SQL. Capable of translating complex data insights into actionable reports for diverse stakeholders while adhering to software engineering best practices.
Highest-signal resume keywords
Python ProgrammingMachine Learning Model DevelopmentAdvanced SQL ProficiencyData Visualization ToolsSoftware Engineering Best Practices
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningDeep LearningStatisticsLinear AlgebraData AnalysisHypothesis TestingData ManipulationPredictive ModelingStatistical AnalysisObject-Oriented Programming
Tools & Technologies
PandasNumPyScikit-LearnSciPyPower BITableauLookerGitGCPAzure
Industry Keywords
Data EngineeringData PipelinesData ApplicationsVersion ControlCollaboration
Tech Stack
Tools & technologiesAzureCloudGoogle Cloud PlatformNumpyPandasPythonScikit-LearnSQLTableau
About the role
Key responsibilities & impact- Explore, clean, and analyze large volumes of structured and unstructured data to identify patterns, anomalies, and opportunities
- Develop, train, and validate predictive and prescriptive Machine Learning models
- Create statistical analyses and hypothesis tests to validate business assumptions
- Translate complex mathematical metrics into reports and dashboards for technical and non-technical stakeholders
- Collaborate with data engineers to structure scalable pipelines
- Deploy models to production following software engineering best practices
- Write clean, modular, and testable code
- Use Git for version control, participate in code reviews, and deploy models and data applications in collaboration with engineering and MLOps teams
Requirements
What you’ll need- Experience with Python (Pandas, NumPy, Scikit-Learn, SciPy) or R
- Proficiency in data querying and manipulation tools: advanced SQL
- Hands-on experience with Machine Learning and Deep Learning frameworks
- Strong knowledge of Statistics (probability, regression, A/B testing) and Linear Algebra
- Experience with data visualization tools (Power BI, Tableau, or Looker)
- Experience with software engineering (Git, GCP and Azure cloud platforms, object-oriented programming)
Benefits
Comp & perks- Health and dental insurance
- Home office allowance
- Meal allowance
- Birthday day off
- Health and wellness program
- Individual Development Plan (IDP)