Data Scientist

About this role

Role & responsibilities A data scientist bridges the gap between complex data and business strategy by turning raw, unstructured information into predictive models and actionable insights. [1, 2]Core Responsibilities

• **Data Collection and Preparation:** Spend a significant portion of time (often 70% to 90%) gathering, cleaning, wrangling, and transforming raw datasets using tools like SQL and Python. [1, 2]
• **Exploratory Data Analysis (EDA):** Investigate data to spot trends, anomalies, correlations, and missing values before building models. [1, 2]
• **Predictive Modeling and Machine Learning:** Design, train, and test algorithms, statistical models, and artificial intelligence systems to forecast future outcomes (such as customer churn, fraud, or sales trends). [1, 2, 3]
• **Model Evaluation and Deployment:** Validate model performance using metrics like precision, recall, and F1 scores, then help push these models into production environments. [1]
• **Data Visualization and Storytelling:** Build dashboards, charts, and reports (using tools like Tableau, Power BI, or Matplotlib) to communicate technical findings to non-technical stakeholders. [1, 2]
• **Stakeholder Collaboration:** Work closely with business leaders, product managers, and data engineers to define goals, frame problem statements, and translate data into business decisions. [1, 2]

Preferred candidate profile A data scientist bridges the gap between complex data and business strategy by turning raw, unstructured information into predictive models and actionable insights. [1, 2]Core Responsibilities

• **Data Collection and Preparation:** Spend a significant portion of time (often 70% to 90%) gathering, cleaning, wrangling, and transforming raw datasets using tools like SQL and Python. [1, 2]
• **Exploratory Data Analysis (EDA):** Investigate data to spot trends, anomalies, correlations, and missing values before building models. [1, 2]
• **Predictive Modeling and ...