Senior Data Scientist
2 months ago
The Senior Data Scientist will play a pivotal role in shaping the data strategy and driving data-driven decision-making processes within the organization.
This position requires a visionary data scientist who collaborates with cross-functional teams, leverages advanced analytical techniques to solve complex business problems, and helps to mentor junior members of the analytics team.
The ideal candidate will have a strong background in data science, excellent interpersonal skills, and a passion for innovation.
Key Responsibilities- Collaborate with stakeholders to identify business challenges and opportunities that can be addressed through data science to improve key business outcomes.
- Design, develop, and implement advanced statistical models and machine learning algorithms to extract insights from large datasets.
- Oversee the end-to-end data science project lifecycle, from data collection and preprocessing to model deployment and monitoring.
- Communicate complex analytical concepts and results to non-technical stakeholders in a clear and concise manner.
- Mentor a more junior analysts and data scientists, providing guidance and support in developing analytical models and solutions.
- Stay abreast of the latest industry trends and advancements in data science and incorporate them into the team's work.
- Collaborate with IT and data engineering teams to integrate data science solutions into existing systems and workflows.
- Partner with Innovation and Digital transformation teams to architect and build analytics engines capable of driving real-time personalized insights using analytic models.
- Apply machine learning models and AI to help mitigate fraud at the credit union.
- Leverage generative AI capabilities and apply solutions to address complex business problems.
- Perform other duties as assigned.
- Undergraduate or advanced degree in Mathematics, Statistics, Computer Science, or a related field.
- Knowledge and experience in applying statistical and machine learning methods including regression, classification, clustering, decision trees, and neural networks.
- 6-10 years' experience in developing, deploying, and managing analytical and machine learning models in a production environment.
- Proven track record of successfully leading data science projects from conception to completion.
- Natural sense of curiosity; being able to self-motivate and proactively find unique or actionable insights and solutions leveraging data.
- Ability to understand business needs and become a leader in enabling data-driven business decisions while also having the ability to work successfully in a team environment.
- Extensive experience with machine learning frameworks and libraries (e.g., Scikit-learn, XGBoost).
- Extensive experience in a statistical programming language such as Python or R.
- Experience with building machine learning and AI models in a cloud environment preferably using Databricks.
- Excellent problem-solving skills and the ability to think critically and strategically.
- Comfortable working in a dynamic environment with multiple concurrent projects.
- Ability to visualize in advance rough requirements and process necessary to implement new production data science applications.
- Empathy and passion for leading junior team members through complex analytical projects.
- Strong communication skills with ability to present ideas and concepts to diverse audiences.
- Familiarity and experience working with relational databases and SQL.
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