Data Scientist at Estrada International Staffing Solutions

Job Overview: As a Data Scientist, you will play a pivotal role in leveraging data and machine learning techniques to extract actionable insights, develop predictive models, and enhance our digital financial services offerings. You will collaborate with cross-functional teams to drive data-driven decisions and continuously innovate in the financial services sector.

Key Responsibilities:

Data Analysis and Exploration:

• Collect, clean, and preprocess large datasets from various sources.
• Perform exploratory data analysis to uncover patterns, trends, and anomalies.
• Develop a deep understanding of the financial services industry and our data ecosystem.

Predictive Modeling:

• Design and implement machine learning models for tasks such as credit risk assessment, fraud detection, customer segmentation, and recommendation systems.
• Fine-tune and optimize models for accuracy and performance.
• Conduct A/B testing and experiments to validate model effectiveness.

Data Visualization:

• Create informative and visually appealing data visualizations to communicate insights to both technical and non-technical stakeholders.
• Build interactive dashboards using tools like Tableau, Power BI, or similar.

Feature Engineering:

• Identify and engineer relevant features to improve model performance.
• Collaborate with data engineers to develop scalable data pipelines for model deployment.

Collaboration and Insights:

• Collaborate with cross-functional teams including product, marketing, and IT to identify opportunities for data-driven improvements.
• Provide actionable insights and recommendations based on data analysis and modeling results.
• Communicate complex findings in a clear and understandable manner.

Model Deployment and Monitoring:

• Deploy models into production environments and ensure their ongoing performance and accuracy.
• Implement model monitoring and maintenance procedures.

Qualifications:

• Bsc. in Data Science, Computer Science, Statistics, or a related field.
• Proven experience as a Data Scientist in the financial services or fintech industry.
• Proficiency in programming languages such as Python or R.
• Strong knowledge of machine learning techniques, including supervised and unsupervised learning.
• Experience with data visualization tools and libraries.
• Knowledge of big data technologies (e.g., Hadoop, Spark) is a plus.
• Strong problem-solving skills and the ability to work on complex, unstructured problems.
• Excellent communication and presentation skills.
• Ethical considerations and awareness of data privacy and security regulations.