#2026-19677
eling, machine learning, and data analysis with strong problem‑solving and communication skills. This role contributes to high‑impact analytical initiatives and helps elevate analytical practices within project teams while remaining primarily focused on hands‑on modeling and technical delivery.
Responsibilities
Responsibilities - Advanced Analytics & Modeling
Define modeling approaches and analytical frameworks for complex or ambiguous problems where established solutions do not yet exist.
Apply predictive modeling, forecasting, classification, clustering, and other advanced analytics techniques to large datasets.
Explore and integrate diverse data sources including transactional, behavioral, demographic, geospatial, and operational data.
Build and validate models using best practices for feature engineering, experimentation, and model evaluation.
Translate analytical findings into clear insights and recommendations for business stakeholders.
Responsibilities - Technical Contribution
Develop production‑ready analytical models and support their integration into data platforms and business workflows.
Identify modeling risks early, including bias, data limitations, drift, and statistical assumptions that could impact model validity.
Collaborate with data engineers and analytics teams to ensure data quality, model reliability, and scalable implementation.
Contribute to the development of reusable analytical frameworks, code libraries, and modeling workflows.
Support the evaluation and selection of appropriate analytical techniques and tools for specific use cases.
Document analytical approaches, model assumptions, and results to ensure reproducibility and transparency.
Responsibilities - Cross‑Functional Collaboration
Partner with business stakeholders to understand analytical needs and translate business questions into data science solutions.
Communicate complex analytical results in a clear and concise manner to both technical and non‑technical audiences.
Contribute to cross‑functional analytics initiatives and collaborate with engineering, product, and analytics teams.
Provide guidance and knowledge sharing on modeling approaches and analytical methods within project teams.
Required Qualifications (Knowledge, Skills, & Abilities)
6+ years of experience in data science, machine learning, or advanced analytics.
Strong understanding of statistical modeling, machine learning algorithms, and predictive analytics.
Proficiency in Python and SQL for data analysis and model development.
Experience working with large datasets and modern data platforms.
Strong problem‑solving, analytical thinking, and communication skills.
Preferred Qualifications (Knowledge, Skills, & Abilities)
8+ years of experience in data science, machine learning, or advanced analytics.
Experience with machine learning frameworks such as PyTorch, TensorFlow, or similar tools.
Experience with distributed data processing frameworks such as Spark.
Exposure to cloud‑based analytics platforms such as AWS, Azure, or GCP.
Experience applying advanced analytics techniques such as geospatial analysis, optimization, or network modeling.
Required Years of Experience
6
Preferred Years of Experience
8
Travel Requirements
10%
Required Level of Education
Bachelor's Degree
Preferred Level of Education
Master's Degree
Major/Concentration
Statistics, Computer Science, Applied Mathematics, Data Science, Engineering, or a related quantitative field.
Relocation Assistance Provided
No