Lead Data Analyst - SQL/Python (8-10 yrs)

Responsibilities :

- Analyze large datasets related to mortgage/housing finance, identifying trends, patterns, and anomalies.

- Translate complex data into clear, concise, and actionable insights for stakeholders at all levels.

- Develop and maintain comprehensive reports and dashboards to track key performance indicators (KPIs).

- Design, develop, and maintain efficient SQL queries to extract, transform, and load (ETL) data from various sources.

- Ensure data accuracy, integrity, and consistency across all platforms.

- Collaborate with data engineers to optimize data pipelines and infrastructure.

- Apply statistical techniques to perform in-depth analysis and identify key drivers of business performance.

- Develop and implement predictive models using Python or R to forecast trends and support strategic decision-making.

- Evaluate model performance and refine models to improve accuracy and reliability.

- Create compelling data visualizations using Tableau and Power BI to communicate insights effectively.

- Develop interactive dashboards and reports to provide real-time visibility into key metrics.

- Present findings and recommendations to stakeholders through clear and concise presentations.

- Mentor and guide junior analysts, fostering a collaborative and high-performing team environment.

- Collaborate with cross-functional teams, including product, marketing, and operations, to understand business needs and deliver data-driven solutions.

- Lead data-related projects and initiatives, ensuring timely and successful completion.

- Maintain a strong understanding of the mortgage/housing finance industry, including market trends, regulatory requirements, and competitive landscape.

- Apply industry knowledge to identify relevant data sources and develop insightful analyses.

Job Requirements :

- Experience : 8-10 years of experience in data analytics, with a significant portion of that experience within the mortgage or housing finance industry.

- Expertise in SQL for data extraction and manipulation.

- Proficiency in Python or R for statistical analysis and predictive modeling.

- Advanced skills in data visualization tools such as Tableau and Power BI.

- Experience with statistical analysis and predictive modelling.

Education :

- Bachelor's degree in a quantitative field such as statistics, mathematics, economics, computer science, or a related discipline. Master's degree preferred. -

Preferred Qualifications :

- Experience with cloud-based data platforms (e.g., AWS, Azure, GCP).

- Knowledge of machine learning techniques and algorithms.

- Experience with data warehousing and data modeling concepts.

- Experience with mortgage servicing data.