2 дня назад
Data Scientist (Fintech)
67 500 - 112 500$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Scientist (Fintech): Building predictive models and advanced analytics solutions for financial services clients with an accent on credit risk, fraud, insurance, marketing, and large-scale data analysis. Focus on designing repeatable analytical frameworks, validating models, translating findings into business recommendations, and presenting insights to technical and non-technical audiences.
Location: Chicago, Illinois; hybrid work with in-person responsibilities at an assigned office at least two days per week
Salary: $67,500–$112,500 annually
Company
provides data and analytics solutions that help financial institutions and other organizations manage risk, prevent fraud, and make informed business decisions.
What you will do
- Develop predictive models and advanced analytics solutions for credit risk, fraud, insurance, and marketing use cases.
- Lead analytics engagements from project design and development through implementation, validation, and client presentation.
- Partner with internal stakeholders, sales teams, and financial services clients to identify opportunities for data-driven business value.
- Perform descriptive, predictive, and prescriptive analyses using large-scale datasets.
- Translate analytical findings into actionable recommendations for technical and non-technical audiences.
- Build data extraction, segmentation, statistical analysis, and repeatable analytical processes that improve efficiency and scalability.
Requirements
- Master’s degree or PhD in statistics, applied mathematics, financial mathematics, computer science, engineering, operations research, or another highly quantitative field.
- At least one year of experience in analytics, data science, statistical modeling, or quantitative analysis.
- Understanding of U.S. financial services risk management practices and data-driven business decisions.
- Experience in financial services, insurance, fraud, credit risk, digital marketing, or a related industry.
- Proficiency with Python or R, SQL, large datasets, and distributed platforms such as Hive and Spark.
- Knowledge of machine learning, predictive analytics, statistical modeling, and business intelligence techniques.
Nice to have
- Experience with credit bureau data, credit risk models, or financial services analytics.
- Exposure to Java or C/C++.
- Client-facing consulting or analytics advisory experience.
- Knowledge of fraud, insurance, or marketing analytics solutions.
Culture & Benefits
- Hybrid work environment with flexibility and collaboration across global teams.
- Medical, dental, and vision coverage with HSA and FSA options from day one.
- 401(k) with employer match, employee stock purchase plan, tuition reimbursement, and career coaching.
- Paid parental leave, caregiver support, adoption assistance, and fertility planning coverage.
- Paid holidays, flexible or paid time off, commuter benefits, wellness programs, and employee assistance resources.
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