Objective: Translate business problems into data science questions with clear success criteria

Breakdown:

• 15% to 20% of project time
• Months 1-3 of an 18-month project timeline

Overview: In this phase, you'll identify key stakeholders, define the project scope, and clarify constraints. This is where data science efforts are aligned with strategic goals and measurable outcomes. A strong foundation here ensures that the entire project remains focused, relevant, and actionable.

Objective: Collect and explore data to understand what's available and identify gaps

Breakdown:

• 10% to 20% of project time
• Months 2-5 of an 18-month project timeline

Overview: In this phase, you will document data types, sources, and collection methods to build a clear picture of what you're working with. You will assess data quality and conduct initial exploration to uncover patterns, anomalies, and potential issues. These insights will guide decisions in later phases, especially data preparation and modeling.

Objective: Create the final dataset for modeling by cleaning, transforming, and integrating data

Breakdown:

• 40% to 60% of project time
• Months 4-12 of an 18-month project timeline

Overview: In this phase, you will address data quality issues to ensure the dataset is ready for effective modeling. This includes handling missing values, normalizing formats, validating entries, and checking for consistency across sources. The goal is to produce a clean, well-structured dataset that supports accurate and reliable analysis.

Objective: Apply various techniques to build and test predictive models

Breakdown:

• 10% to 20% of project time
• Months 8-14 of an 18-month project timeline

Overview: In this phase, data is transformed into actionable insights. You will apply statistical techniques (e.g., hypothesis testing, significance testing, correlation, and regression analysis) to uncover relationships and patterns. You will also select, build, and validate predictive models to ensure they meet performance standards and are ready for evaluation.

Objective: Assess whether models meet business objectives before deployment

Breakdown:

• 5% to 15% of project time
• Months 12-16 of an 18-month project timeline

Overview: In this phase, you will validate the model against the original success criteria using performance metrics and key performance indicators (KPIs). You will also evaluate whether the solution is viable for deployment, identify any constraints or limitations, and communicate findings clearly to stakeholders to support informed decisions.

aa

Objective: Integrate models into business processes and ensure ongoing maintenance

Breakdown:

• 5% to 15% of project time
• Months 15-18 of an 18-month project timeline

Overview: In this phase, you will focus on automating workflows, integrating systems, and setting up monitoring tools to ensure models perform reliably over time. Retraining may be necessary as data evolves. Planning for maintenance and continuous improvement is essential. Strong communication and presentation skills are also key, allowing you to share results with stakeholders to support informed decision-making.