11 часов назад
Data Scientist (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Scientist (AI): Developing and deploying predictive models, machine learning, and AI solutions for risk, fraud, marketing, and portfolio management in financial services with an accent on end-to-end model lifecycles, NLP, experimentation, and MLOps. Focus on building production-ready models, preparing complex datasets, translating ambiguous business problems into analytical frameworks, and converting results into actionable product recommendations.
Location: Atlanta, Georgia, United States
Company
provides technology and financial services solutions, with a focus on shaping the future of fintech.
What you will do
- Design, develop, validate, deploy, and monitor advanced analytics, machine learning, and AI solutions for measurable business outcomes.
- Prepare and assemble datasets from standard and novel sources for end-to-end analytical solutions.
- Apply predictive analytics, NLP, Generative AI, and Agentic AI to problems across payments and financial services.
- Design experiments, hypothesis-testing frameworks, and statistical analyses for business and product decisions.
- Establish best practices for data science, feature engineering, model governance, experimentation, and MLOps.
- Translate analytical results into actionable product recommendations for internal and external stakeholders.
Requirements
- Master’s degree or higher in mathematics, computer science, engineering, operations research, statistics, or a related quantitative discipline.
- 1–3 years of experience developing and deploying end-to-end machine learning, predictive analytics, and data science solutions.
- Strong proficiency in Python and SQL.
- Hands-on experience with data wrangling, feature engineering, model development, and production or near-production deployment.
- Experience with data visualization and business intelligence tools such as Tableau or equivalent.
- Strong analytical, problem-solving, and cross-functional collaboration skills.
Nice to have
- Experience with Spark, PySpark, Databricks, MLflow, Model Registry, and MLOps workflows.
- Experience deploying cloud-native machine learning solutions in AWS environments.
- Familiarity with Transformer Models, Agentic AI, model governance, and regulatory compliance in financial services.
Culture & Benefits
- Collaborative, open, entrepreneurial, and inclusive work environment.
- Ongoing learning and development opportunities.
- Opportunities to contribute to the community.
- Competitive salary and benefits.
- US-based positions may require a drug test after a conditional offer.
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