What are the responsibilities and job description for the Senior Manager Data Science position at WhiteCrow Research?
About WhiteCrow
We are global talent research, insight, and sourcing specialists with offices in the UK, USA, Singapore, Malaysia, Hong Kong, Dubai, and India. Our international reach has helped us to understand and penetrate specialist markets at a global level. In addition to this, our service is also extended to complement our client’s in-house talent acquisition teams.
About our client
Our client is a leading global provider of legal, regulatory and business information and analytics that help customers increase productivity, improve decision-making and outcomes, and advance the rule of law around the world.
They help lawyers win cases, manage their work more efficiently, serve their clients better and grow their practices. They assist corporations in better understanding their markets, monitoring their brands and competition, and in mitigating business risk. They collaborate with universities to educate students, and support nation-building with governments and courts by making laws accessible and strengthening legal infrastructures. They partner with leading global associations and customers to collect evidence against war criminals and provide tools to combat human trafficking.
As a Senior Manager Data Science, you will be responsible for...
- Managing a team of data scientists and engineers to design, develop, and deploy advanced AI solutions
- Leading the development of AI and machine learning models to solve business problems
- Researching, building, and deploying models based on shallow and deep machine learning
- Training robust NLP-based models on large datasets
- Collaborating with cross-functional teams to align AI solutions with business goals and customer needs
- Designing APIs for disseminating data science outputs
- Overseeing the scaling of production systems to meet growing demands
What you already have...
- Deep understanding of machine learning algorithms, including deep learning, gradient boosting, and random forests.
- Experience working directly with large language models and Transformer based architectures including BERT, RoBERTa, T5 etc.
- Working knowledge of applying recent LLMs including ChatGPT, GPT 3.5, OPT, BLOOM, etc.
- Experience with reinforcement learning, prompt engineering, hallucination mitigation.
- Working understanding of the business risks associated with applying LLM in a business.
- Experience working with large datasets and distributed computing systems (e.g., Hadoop, Spark).
- Strong coding skills in Python or another programming language.
- Excellent communicator, with the ability to translate complex technical concepts to non-technical stakeholders.
- Strong problem-solving skills and the ability to think outside the box.