Location: Hybrid (Ohio Preferred)
Duration: 6-Month Contract
We are seeking a passionate, data-driven Senior Data Scientist to join a high-performing Enterprise Analytics team focused on driving business growth through advanced analytics, experimentation, and actionable insights. This role partners closely with stakeholders across Product, Marketing, Digital, Finance, Operations, and Technology to uncover opportunities within customer, product, channel, and digital data.
The ideal candidate combines strong analytical and technical capabilities with excellent communication skills and a passion for data storytelling, optimization, and business impact. This is a highly visible role with the opportunity to influence strategic decision-making across the organization.
Apply advanced analytics techniques to extract business value from large and complex datasets.
Design and execute large-scale experiments and data-driven analyses to solve business problems.
Build predictive and statistical models to identify trends, opportunities, and actionable insights.
Research and evaluate emerging machine learning, deep learning, and AI methodologies.
Develop and refine model requirements, algorithms, and analytical frameworks.
Translate analytical findings into clear recommendations for business and product stakeholders.
Create intuitive visualizations and dashboards to communicate insights effectively.
Partner with cross-functional teams throughout the project lifecycle, from ideation through implementation.
Present findings and recommendations to technical and non-technical audiences, including senior leadership.
Master's degree in Computer Science, Information Systems, Statistics, Applied Mathematics, Engineering, Operations Research, Decision Sciences, or another STEM-related field
OR
Bachelor's degree with 3+ years of professional experience in Data Science, Analytics, or a related field
Strong experience with:
Python
SQL
R / RStudio
SAS
NoSQL databases
Experience performing statistical analysis, predictive modeling, and advanced analytics.
Ability to work with large, structured and unstructured datasets.
Experience with machine learning and predictive modeling techniques.
Knowledge of supervised and unsupervised learning methodologies.
Experience with cloud-based machine learning platforms such as AWS SageMaker.
Experience with machine learning frameworks including:
TensorFlow
Scikit-learn
Caret
Familiarity with:
Big data tools and technologies
Data pipelines and data engineering concepts
Web scraping techniques
Model deployment and monitoring
Strong understanding of statistical concepts including:
Bayesian Inference
Linear & Non-Linear Regression
Hierarchical/Multi-Level Modeling
Mixed Models
Experience within Banking, Financial Services, FinTech, or other highly regulated industries is a plus.
Naturally curious with a passion for solving complex business problems through data.
Strong communicator capable of translating technical findings into business recommendations.
Comfortable working in ambiguous environments and managing multiple priorities.
Collaborative team player who can effectively partner with technical and business stakeholders.
Demonstrated ability to influence decision-making through data-driven insights.
Experience working in customer-focused organizations is highly preferred.
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