Senior Data Scientist #2397
Position Summary:
Our partner, an innovative leader in financial services known for developing forward-thinking solutions to improve financial lives is seeking a skilled Data Scientist to join our team. The ideal candidate will leverage their expertise in statistics, machine learning, and data analysis to extract insights from large datasets and help drive data-informed decisions across the organization. You will collaborate closely with audit, credit, data, and technology professionals.
Experience and Education:
- BS in Computer Engineering or Computer Science, Statistics, Informatics or related experience/field
- 5+ years of experience as a Data Scientist or in a similar analytical role.
- Advance skills in Microsoft Excel
- Expertise in programming languages such as Python, SQL or Tableau.
- Proficiency with machine learning frameworks and libraries (e.g., scikit-learn, TensorFlow, PyTorch).
- Strong knowledge of statistical analysis, experimental design, and data mining techniques.
- Experience with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Google Cloud, Azure).
- Experience with any of the following: DataRobot, Instabase, and UIPath (a plus).
Skills and Strengths:
- Data
- Data Architecture
- Data Extraction
- Data Modeling
- Data Analysis
- Data Pipelines
- Data Governance
- Data Quality Management
- Microsoft Excel
- SQL
- SQL Queries
- Python or similar (R, JavaScript, Java, others)
- Data Visualization tools as Tableau, Power BI, Alteryx, others
- Data automated solutions implementation
- Statistical Analysis
- Risk Management
- Financial Management
- Solution Delivery Process
- Concept Testing
- Project Management
- Mentorship
Primary Job Responsibilities:
- Lead the design and implementation of advanced machine learning models and algorithms to solve complex business problems.
- Analyze large and diverse datasets to extract actionable insights and drive data-informed decision-making.
- Collaborate with product managers, engineers, and other stakeholders to define data requirements and analytics strategy.
- Mentor and guide junior data scientists and analysts in best practices and methodologies.
- Develop data visualizations and dashboards to effectively communicate findings and recommendations to both technical and non-technical audiences.
- Conduct statistical analysis and A/B testing to validate model performance and business impact.
- Stay abreast of the latest developments in data science and machine learning technologies and methodologies.
