Data Science

2 days ago

Fatih, Istanbul, Turkey AXA Türkiye Full time

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AXA is the leading insurance brand worldwide, with a presence in 54 countries, and 153,000 employees serving the needs of 105 million customers. We are transforming from payer to partner for our client, with a strong focus on risk prevention. We protect and advise our clients at every step in their lives, by offering products and services which satisfy their needs in the areas of insurance, personal protection, saving and asset management. As one of the largest global insurers, our purpose is to act for human progress by protecting what matters.

Proud to be part of the AXA Group, a global insurance brand and a worldwide leader in financial services, AXA Insurance businesses across Turkey. AXA Sigorta was founded in 1968 headquartered in Istanbul and has regional offices in Turkey, and Turkish Republic of Northern Cyprus. Acting as a subsidiary of AXA Group it provides insurance, personal protection, savings and estate planning solutions for individuals, small or medium-sized businesses and large corporations in Turkey.

For AXA Turkey, supporting diversity and inclusion values form an integral part of everything we do. For us, it's about bringing together the best talent, helping people to realise their full potential by being 100% themselves at work and delivering outstanding service to everyone – regardless of difference.

Qualifications

  • Bachelor's degree in Advanced Mathematics, Statistics, Data Science or a similar field of study, or Master's degree in fields such as Artificial Intelligence, Machine Learning, Data Science.
  • 8+ years of experience in building, deploying, and evaluating real-world machine learning solutions.
  • 2+ years of leadership experience.
  • Proven track record of working with programming languages (e.g., Python, Spark, PySpark), SQL, and NoSQL.
  • Expertise in ML/AI libraries such as scikit-learn, TensorFlow, PyTorch, and SciPy.
  • Hands-on experience with LLMs, transformer models, and generative AI frameworks (e.g., OpenAI, HuggingFace, LangChain).
  • Experience with modern AI and MLOps platforms (e.g., Jupyter, Airflow, Kubernetes, MLflow, HuggingFace).
  • Advanced knowledge of English.
  • Experience working in the insurance industry, particularly with GenAI in real-world applications such as risk assessment, claims automation, and fraud detection.
  • Advanced statistical knowledge and excellent problem-solving skills, with a proven ability to translate data into actionable insights.

Responsibilities

  • Design, build, and optimize machine learning models that optimize commerce payment products.
  • Manage the full lifecycle of ML development, including data collection, feature engineering, model selection, evaluation, and production.
  • Collaborate with engineers to deploy models at scale, ensuring robust A/B testing frameworks to assess the impact on key business metrics.

Data Exploration & Insights

  • Dive deep into subscriber and payment data to uncover patterns and opportunities for growth and retention strategies.
  • Lead exploratory analyses and complex statistical modeling to deliver actionable insights that inform high-stakes business decisions.

Data Storytelling

  • Translate complex data into clear and actionable insights through visualizations, reports, and presentations tailored to both technical and non-technical stakeholders.
  • Drive data-informed decision-making by presenting findings that highlight business implications.

Strategic Collaboration & Leadership

  • Build and foster strong relationships with business partners across commerce, growth, marketing, and engineering.
  • Collaborate with other data teams to improve our data infrastructure, including models, visualizations, and experimentation capabilities.
  • Mentor and grow a high-performing team of data scientists, creating an environment that encourages learning and innovation.
Seniority level
  • Mid-Senior level
Employment type
  • Full-time
Job function
  • Finance, Accounting/Auditing, and Analyst
  • Industries: Insurance and Banking
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