You will collaborate closely with a team comprising data scientists, data engineers, product developers, and analytics-focused consultants.
You will work on topics such as descriptive analytics, predictive models (e.g., boosted trees), and large language models (LLMs), particularly for segmentation use cases. Additionally, you will design and deliver products that adhere to MLOps best practices, ensuring they are both maintainable and deployable. By doing so, you will help bring advanced analytics capabilities into one of McKinsey’s flagship products, named "Wave". Your work will be the backbone for how McKinsey runs future Transformations, leveraging data science assets, to improve the odds of success for our clients.
In this role, you will be responsible for the following, as the primary focus:
- Advanced insight generation:transforming complex business questions into statically relevant analyses and these analyses into easy to digest insights. Delivering this through well documented and tested pipelines, that allow easy collaboration with other team members.
- Upholding technical excellence:Together with the tech lead(s) define how to build, maintain and scale our pipelines. Often piloting new technical approaches & automation. Using your business understanding to critically review model results, trends, analyses and classifications.
- Coach & help other colleagues:Coach & help you peers when needed, we deliver as a team.
- Machine learning model development:Lead the design and refinement of statistical models, optimization techniques, advanced machine learning, and predictive models
- LLM optimization and evaluation:Fine-tune and evaluating the performance and efficiency of Large Language Models, leveraging the latest advancements in neural network architectures and machine learning techniques
Your role might also include, as the secondary focus:
- Design & build creative approaches to further optimize accuracy & reduce cost:In addition to optimizing the LLM through prompts and settings, you will design and test alternative approaches, such as pre-filters and non-LLM-based text models, within parallel multi-agent setups.
- Build for scale:Together with the tech lead(s), you will define how to maintain and scale our LLM classifier pipeline. The classifier pipeline will, in the long term, run as a on-demand batch process, and will, once stable, be refactored with scalability in mind.
- Deploying pipelines at scale:Although not core to your role, you will be exposed to cloud deployments & orchestration of our pipelines and can shape these if you have an interest in this field.
- Expert guidance for client teams:You will work closely with global client service teams to deliver high-quality advanced analytics solutions, offering expert guidance to ensure analytical excellence and understanding at client teams.
- Knowledge and research:You will contribute to influential articles, white papers, and research, positioning the firm as a thought leader in analytics and transformation, with a focus on LLMs and predictive modeling