Data Scientist analyzing claims data, optimizing processes and collaborating across departments at Allianz Spain. Utilizing statistical techniques and developing predictive models for operational efficiency.
About the role
- Tech Lead Data Scientist at Aera Technology driving enterprise-level ML solutions with customer focus. Leading data science projects, mentoring junior staff, and integrating AI in customer environments.
Responsibilities
- Act as the senior technical point of contact, driving successful outcomes by identifying, scoping, and leading data science projects that directly address high-value customer problems.
- Measure and report on the business impact (ROI, efficiency gains) of deployed models.
- Ensure rigorous testing and validation of all new data science features and model deployments.
- Design, implement, monitor, and maintain scalable, production-grade Data Science systems.
- Research and evaluate the latest in Machine Learning, Generative AI, and advanced statistical models for new feature development.
- Actively scout, evaluate, and implement the latest advancements in Data Science, Machine Learning (MLOps, LLMs/Generative AI), and AI to maintain Aera’s technical edge.
- Maintain a zero-tolerance policy for delayed customer resolution related to Data Science models and pipelines, working closely with Support, Customer Success and Product teams to resolve issues and implement robust, long-term solutions.
- Directly lead and mentor a small, high-impact team (2-3 members) including Data Scientists, Senior Data Scientists, and Interns, setting technical standards, guiding project execution, and fostering individual career growth.
- Translate customer feedback and cutting-edge research into actionable product features and technical specifications for the engineering and product teams.
Requirements
- Master’s or Bachelor’s Degree in Computer Science, Engineering, Mathematics, Statistics, or a related quantitative field with a focus on Machine Learning/Deep Learning/AI.
- 7+ years of progressive professional experience as a Data Scientist or Machine Learning Engineer, ideally in a B2B SaaS or product development setting.
- Proven, hands-on experience designing, developing, and deploying systems utilizing the latest advancements in AI (e.g., MLOps practices, Generative AI, vector databases, or transformer models).
- Strong experience with the full ML lifecycle, including translating research models into scalable, production-ready services using modern software development practices.
- Exceptional proficiency in SQL and Python; able to write high-quality, high-performance, and maintainable code.
- Experience with distributed systems and ML frameworks such as Dask, Ray, or Spark.
- Familiarity with production ML services like Kubeflow, Sagemaker, or similar cloud-native MLOps tools is a significant advantage.
- Demonstrated experience in leading projects, setting technical direction, and mentoring or supervising junior data professionals. Experience leading teams or performing hiring is a strong plus.
Benefits
- Comprehensive medical
- Group Medical Insurance
- Term Insurance
- Accidental Insurance
- Paid time off
- Maternity leave
- Unlimited access to online professional courses
- People manager development programs
- Flexible working environment
- Fully-stocked kitchen with snacks and beverages
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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