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Junior Data Scientist
FCamara Consulting & Training. Design, develop, and maintain predictive models for the business.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and developing predictive models, enhancing machine learning capabilities, and transforming data into actionable business intelligence. Proficient in data ingestion, transformation, and validation within data lake and data warehouse environments, with a strong focus on data quality and governance.
Highest-signal resume keywords
Python Applied To Data EngineeringAdvanced SQLAWS Cloud (AWS Glue, Amazon Redshift, Amazon S3)Dimensional ModelingData Quality
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Predictive ModelingMachine LearningData IngestionData TransformationData ValidationExploratory AnalysisStatistical ModelingData ArchitectureData GovernanceData Cataloging
Soft Skills
CollaborationCommunication
Tools & Technologies
PandasNumPyPower BITableauLookerGitApache AirflowPySpark
Industry Keywords
Financial SectorCredit OperationsBusiness Intelligence
Tech Stack
Tools & technologiesAirflowAmazon RedshiftApacheAWSCloudNumpyPandasPySparkPythonSQLTableau
About the role
Key responsibilities & impact- Design, develop, and maintain predictive models for the business.
- Enhance Machine Learning models to support decision-making.
- Create strategies to transform data repositories into business intelligence and build statistical models.
- Develop data ingestion, transformation, and validation routines in data lake and data warehouse environments.
- Collaborate with business, operations, and technology teams to understand needs and translate requirements into efficient data structures.
- Conduct exploratory analyses, identify patterns, and support decision-making with data-driven insights.
- Document models, transformation rules, data dictionaries, and ingestion workflows.
- Support squads and stakeholders in developing indicators, metrics, and analytical views.
- Monitor database performance and propose continuous improvements in data architecture, governance, and quality.
Requirements
What you’ll need- Python applied to data engineering and data science.
- Pandas and NumPy for data manipulation and analysis.
- Advanced SQL for querying, modeling, and optimization.
- Experience with AWS Cloud, including AWS Glue, Amazon Redshift, and querying data stored in Amazon S3 is a plus.
- Knowledge of dimensional modeling (facts, dimensions, star schema).
- Experience in the financial sector, particularly in credit operations or products, is a plus.
- Familiarity with Power BI, Tableau, or Looker is a plus.
- Knowledge of Git and software development best practices is a plus.
- Understanding of data quality and data cataloging is a plus.
- Knowledge of Apache Airflow for pipeline orchestration is a plus.
- Knowledge of PySpark for distributed processing and handling large volumes of data is a plus.
Benefits
Comp & perks- No benefits, additional benefits, or extra compensation are specified in the posting.