Lead Applied Data Scientist
1 week ago
Lead Applied Data Scientist - Insurance Client
Be part of something groundbreaking
We are currently partnering with a global leader in the insurance space on their journey towards reshaping the core of their business. To achieve this, our client is making a long-term commitment to a brand-new, innovative Generative AI team, designed to explore new possibilities for how artificial intelligence can be applied in insurance and beyond.
This team is central to their vision of the future and the core of their business offering. They will incorporate best-in-class engineering and product management principles, and your guidance and collaboration will be critical to its success. If you're excited by the opportunity to create meaningful impact at scale, we'd love to hear from you.
As a Lead Applied Data Scientist, you will have the opportunity to be at the forefront of groundbreaking Generative AI initiatives, leveraging and further developing your skills to shape the future of insurance. If you're looking for a place to grow your career, where your contributions will shape the future of the industry, this is a great opportunity for you.
How you will create impact
As a Lead Applied Data Scientist, you will support the development and delivery of innovative AI solutions, helping the firm to become a leader in applying Generative AI to solve complex business challenges. This is an exciting opportunity to shape a newly formed team with the resources and support to explore fresh, creative approaches. With your expertise, we'll transform how data drives innovation, creating smarter, more efficient, and personalized solutions that set new standards for the industry.
Your responsibilities include:
- Own the end-to-end development and deployment of data science and GenAI/ML models from conceptualization to operational rollout, while ensuring that all solutions align with ethical and regulatory standards.
- Collaborating with teams across the business-product managers, business leaders, engineers, and others-to create data-driven solutions that make a difference.
- Fostering a collaborative and innovative environment where knowledge-sharing and creativity thrive among the data science community
- Utilize Retrieval-Augmented Generation (RAG) and Prompt Engineering and few-shot techniques to enhance LLM's performance on specific tasks
- Build evaluation frameworks to measure LLMs efficacy, ground truth dataset quality, and guide product development roadmap
- Driving continuous improvement of AI capabilities by staying at the forefront of emerging technologies and identifying how they can enhance our operations.
- Contributing to day-to-day direction of multiple components of Data Science activities
Required applied skills
- You bring significant experience as an applied data scientist and/or data engineer
- You bring recent hands-on experience with Retrieval-Augmented Generation (RAG), prompting and model fine-tuning
- You have experience across the full ML-Ops lifecycle
- Ideally applied experience in financial services or insurance
- You have deep expertise in data science techniques such as deep learning, machine learning, statistical modelling, NLP
- You have strong data engineering skills in Python and PySpark
- You are proficient with one or more modern AI/ML platforms (e.g. Palantir Foundry, AWS SageMaker, Azure ML or Snowflake), and are experienced with cloud-based cognitive services
- Strong experience using key Python packages for data wrangling, machine learning and deep learning
- Experience using GitHub code version
NOTE: This role is a permanent position with one of our clients within the insurance industry. You will NOT be employed by BCG.
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