Description Overview
We are seeking a highly analytical Data Scientist / Advanced Analytics Specialist to leverage advanced analytics, machine learning, and statistical modeling techniques to extract insights from complex business data. This role focuses on building data-driven models, conducting large-scale experimentation, and influencing business decisions through actionable insights.
The ideal candidate is intellectually curious, thrives in ambiguous problem spaces, and enjoys applying cutting-edge analytics techniques to real-world business challenges.
Key Responsibilities
- Apply advanced analytics methods to extract value from structured and unstructured business data
- Design and execute large-scale experiments and develop data-driven models to answer complex business questions
- Conduct research on emerging techniques and tools in machine learning, deep learning, and artificial intelligence
- Define requirements used to train, evaluate, and evolve predictive and deep learning models
- Analyze results and present data-based recommendations to product, business, and technical teams
- Influence decision-making through clear, compelling data storytelling and insights
- Support ongoing analytics initiatives and perform additional duties as assigned
Requirements Required Qualifications
Master's degree completed by Spring 2025 in:
- Computer Science
- Information Systems
- Decision Sciences
- Statistics
- Operations Research
- Applied Mathematics
- Engineering
- Or a related STEM discipline
- OR
Bachelor's degree with 3+ years of professional experience in analytics or data science
Hands-on experience with:
- R / RStudio
- Python
- SAS
- SQL / NoSQL
- Strong analytical, quantitative, and problem-solving skills
Preferred Qualifications
- Up-to-date knowledge of machine learning and advanced analytics tools and techniques
- Experience with predictive modeling methodologies
- Ability to work with both structured and unstructured data sources
- Experience conducting statistical analysis using advanced software, scripting languages, and packages
- Exposure to big data tools, scalable data pipelines, and web scraping techniques
- Foundational experience building and deploying predictive models
- Strong understanding of statistical methods including:
- Bayesian networks and inference
- Linear and non-linear regression
- Hierarchical and mixed-effects models
- Experience with cloud-based machine learning platforms (e.g., AWS SageMaker)
- Familiarity with machine learning frameworks such as TensorFlow, scikit-learn, or caret
- Background in financial services or banking is a plus
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