обновлено 2 дня назад
Senior Data Scientist (AI)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Data Scientist (AI): Developing statistical, machine learning, and AI solutions for customer intelligence, forecasting, fraud detection, claims analytics, and strategic decision-making with an accent on time-series modelling, predictive analytics, and production ML. Focus on building customer segmentation and churn models, designing experiments, collaborating with data engineering teams, and monitoring models in production environments.
Location: Ljubljana, Slovenia; hybrid working model
Company
is a global insurer using data, analytics, and AI to improve customer understanding, business performance, and decision-making.
What you will do
- Develop and deploy statistical, machine learning, and AI models for strategic business objectives.
- Design forecasting solutions for customer, operational, and financial KPIs using time-series and predictive modelling.
- Build customer intelligence solutions covering segmentation, lifetime value, retention, and churn prediction.
- Apply machine learning to fraud detection, claims analytics, risk assessment, and related business use cases.
- Explore complex datasets, run experiments such as A/B tests, and create visualizations and dashboards.
- Collaborate with business stakeholders and data engineering teams while supporting production deployment, monitoring, governance, and continuous model improvement.
Requirements
- 6+ years of experience in data science, advanced analytics, and machine learning.
- University degree in Statistics, Mathematics, Computer Science, Engineering, Data Science, or a related quantitative discipline; equivalent experience is acceptable.
- Strong knowledge of statistical modelling, predictive analytics, machine learning, forecasting, and time-series modelling.
- Strong programming skills in Python and/or R, plus SQL, with experience handling large datasets and production data pipelines.
- Understanding of the machine learning lifecycle, including data preparation, validation, monitoring, and performance evaluation.
- Fluent written and spoken English required.
Nice to have
- Experience with Azure-based analytics ecosystems, Databricks, Spark, or similar distributed data processing frameworks.
- Experience with MLOps practices and model deployment frameworks.
- Background in insurance, financial services, or other customer-centric industries.
- Knowledge of responsible AI and model risk management, including bias assessment, documentation, and explainability.
Culture & Benefits
- Hybrid and flexible working arrangements.
- Equal opportunity workplace valuing diversity, individuality, and collaboration.
- Opportunity to contribute to data science best practices, model governance standards, and analytical methodologies.
- Work focused on using data, analytics, and AI to better understand and serve customers.
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