Journeyman Data Scientist:

A Journeyman Data Scientist is typically a mid-level professional who works independently on data science projects, develops predictive models, analyzes complex datasets, and collaborates with stakeholders to support business decisions.

Job Duties

• Collect, clean, and prepare structured and unstructured data from multiple sources.
• Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies.
• Develop, test, and deploy machine learning and statistical models.
• Create predictive analytics solutions to support operational and strategic objectives.
• Design and maintain data pipelines and analytical workflows.
• Build dashboards, reports, and visualizations to communicate findings.
• Validate model performance and recommend improvements.
• Conduct data quality assessments and ensure data integrity.
• Document methodologies, code, and analytical processes.
• Support business units by translating complex data into actionable insights.

Technical Responsibilities

• Apply statistical analysis, machine learning, and data mining techniques.
• Develop algorithms and predictive models using programming languages such as Python, R, or SQL.
• Work with large datasets using cloud and big data platforms.
• Optimize model accuracy, scalability, and performance.
• Implement model monitoring and maintenance procedures.

Business Responsibilities

• Partner with business stakeholders to understand requirements and objectives.
• Present findings and recommendations to technical and non-technical audiences.
• Support data-driven decision-making across departments.
• Identify opportunities for process improvement and automation.

Team Responsibilities

• Collaborate with data engineers, software developers, analysts, and project managers.
• Mentor junior data scientists and analysts.
• Participate in code reviews and knowledge-sharing activities.
• Follow organizational standards, governance, and security requirements.

Required Experience

Clearance Required: Secret or TS/SCI (not sure on this yet)

Education

• Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field.
• Master's degree preferred for some organizations.

Professional Experience

• Typically 3–7 years of experience in data science, analytics, machine learning, or a related field.
• Experience working with large-scale datasets and production environments.
• Proven track record of delivering analytical solutions that drive business outcomes.

Technical Skills

• Programming: Python, R, SQL.
• Machine Learning: Scikit-learn, TensorFlow, PyTorch, XGBoost.
• Data Visualization: Tableau, Power BI, Matplotlib, Plotly.