Sr Statistical Modeler in United States at Jobgether
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Job Description
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Statistical Modeler based in the United States.
This role is centered on designing, developing, and operationalizing advanced statistical and machine learning models that directly support critical risk, fraud, and identity intelligence solutions. You will work across the full modeling lifecycle, translating complex business problems into scalable, production-ready analytical systems. The position combines deep data science expertise with real-world impact, contributing to solutions that improve decision-making, security, and operational efficiency for large-scale enterprise systems. You will collaborate closely with engineering, product, and platform teams in an AI-forward environment that emphasizes experimentation, model iteration, and deployment at scale. The role requires strong technical autonomy, with responsibility for executing end-to-end analytical work while also mentoring junior team members. It is a highly visible position where your models and insights directly influence business outcomes and product innovation.
- Develop and implement advanced statistical, machine learning, and predictive models to solve complex business and product challenges.
- Translate structured and unstructured data into scalable analytical solutions using robust data science methodologies.
- Build, evaluate, and optimize machine learning models across the full lifecycle, ensuring strong performance and production readiness.
- Design and maintain data pipelines and infrastructure that integrate and enable access to diverse internal and external datasets.
- Apply statistical techniques and evaluation frameworks to assess model accuracy, performance, and reliability.
- Collaborate with engineering and product teams to operationalize models within cloud-based production environments.
- Contribute to best practices in coding, testing, version control, and reproducible data science workflows.
- Mentor junior data scientists and serve as a technical expert within the analytics function.
- Communicate complex analytical insights clearly to both technical and non-technical stakeholders.
- Advanced degree (Master’s or higher preferred) in Data Science, Statistics, Computer Science, Mathematics, or related field, or equivalent experience.
- 5+ years of experience in data science, statistical modeling, or applied machine learning roles.
- Strong hands-on experience building, validating, and deploying predictive and machine learning models.
- Proficiency in Python and/or R with libraries such as pandas, NumPy, scikit-learn, XGBoost, and PyTorch.
- Strong SQL skills and experience working with relational and/or cloud-based data platforms.
- Experience working with large-scale structured and unstructured datasets.
- Hands-on experience deploying models in cloud environments such as AWS or Azure, including compute, storage, and monitoring.
- Familiarity with modern AI techniques, including LLM-based solutions, retrieval-augmented workflows, or generative AI applications.
- Experience evaluating and working with neural network-based models.
- Strong understanding of software engineering best practices including version control, testing, and code quality standards.
- Ability to independently execute complex analytical projects within defined scope and deadlines.
- Strong communication skills with the ability to explain technical concepts to non-technical audiences.
- Competitive base salary ranging from $104,900 to $174,700 USD, with potential geographic adjustments.
- Annual performance-based incentive bonus eligibility.
- Comprehensive healthcare coverage including medical, dental, and vision plans.
- Retirement benefits with employer contributions.
- Flexible remote work environment across the United States.
- Paid time off and additional wellness-focused benefits.
- Opportunity to work on high-impact AI and risk analytics solutions at scale.
- Professional development and career growth within an advanced data science organization.