Lead Data Scientist (GenAI)

TL;DR

Lead Data Scientist (GenAI): Managing and mentoring data science teams while leading EAMRM priorities and innovation in GenAI and platform analytics with an accent on big data cloud platforms and advanced modeling techniques. Focus on developing and deploying ML models using Python/PySpark, ensuring regulatory compliance, and collaborating with cross-functional stakeholders to deliver impactful solutions.

Location: Hybrid in Sofia, Bulgaria

Company

Global data and technology company powering opportunities for people and businesses in financial services, fraud prevention, healthcare, automotive, and more, with 22,500 people across 32 countries.

What you will do

• Lead and mentor a team of innovation-focused data scientists, partnering with leaders, engineers, product managers, and external partners to deliver client-impacting solutions.
• Develop and deploy models using Python or PySpark on big data cloud platforms like AWS and Ascend, adhering to model risk management and governance.
• Drive GenAI and platform analytics innovation, crafting advanced ML solutions and prototypes from diverse data sources.
• Collaborate with engineering, research, and data science teams on ML, dashboarding, ad hoc analysis, and AI applications in cloud-native environments.
• Leverage GenAI tools for model development, dissect datasets for insights, and assess internal/external analytic tools.
• Stay ahead of regulatory changes and integrate new data assets/software, gathering client feedback for product evolution.

Requirements

• 7+ years in AI, data science, or predictive modeling, with hands-on experience in complex analytical projects; data science team management preferred.
• Advanced degree in Machine Learning, Data Science, AI, Computer Science, or related quantitative field.
• Proficiency in Python, distributed computing (AWS, Spark/PySpark), statistical modeling, and large data analysis (Hadoop, NoSQL: Hive, HBase, MongoDB, Cassandra).
• Expertise in ML algorithms (XGBoost, GANs, clustering, graph algorithms, hyperparameter tuning).
• Experience with Generative AI tools, rapid prototyping, and client success.
• Proven experience managing analytics or data science teams.

Culture & Benefits

• Personal development with career pathways, unlimited online training, learning materials, and books.
• Excellent work environment with friendly team spirit, flexible hours, and home office opportunities.
• Comprehensive social package: life/health insurance, food vouchers, flex allowance, Multisport card, Sharesave plan, employee assistance, birthday gifts, and more.
• Work-life balance: 25 days vacation, birthday day off, 3 extra paid days for social responsibility events.