Our client, a leading insurance group, is looking for a Senior Data Scientist in the AI / ML space. You will be responsible for designing, developing, and implementing cutting-edge AI/ML models and solutions to drive business growth. You will collaborate with cross-functional teams to leverage the power of data and deliver impactful insights and recommendations.
Key Responsibilities:
Develop and deploy advanced AI/ML algorithms and models: Design, implement, and optimize predictive models, deep learning networks, and recommender systems to solve complex business problems. Utilize state-of-the-art techniques, including natural language processing (NLP), computer vision, and anomaly detection.
Create and manage data integration pipelines: Collect, clean, preprocess, and transform large-scale structured and unstructured data from diverse sources. Collaborate with data engineers to ensure seamless data integration and model performance.
Drive innovation through cloud-based solutions: Leverage cloud platforms to develop scalable and efficient AI/ML solutions. Work closely with cloud architects to architect and deploy data pipelines, infrastructure, and analytics services.
Collaborate with cross-functional teams: Partner with business stakeholders, actuaries, underwriters, and BA/PM/QAs to identify opportunities for AI/ML implementation. Translate business problems into technical requirements and deliver actionable insights.
Conduct research and stay up-to-date with industry trends: Stay abreast of the latest advancements in AI/ML technology, methodologies, and tools. Conduct exploratory data analysis and lead research initiatives to identify potential opportunities for innovation.
Mentor and coach junior data scientists: Provide guidance and support to junior team members. Promote a culture of continuous learning and development within the data science team.
Qualifications:
Master's degree in computer science, statistics, mathematics, or a related field.
Minimum of 5 years of hands-on experience in implementing AI/ML solutions in a professional setting.
Strong programming skills in Python, R, or similar languages. Proficiency in using popular AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
Experience in cloud-based technologies (e.g., AWS, Azure, Google Cloud Platform) and big data frameworks (e.g., Hadoop, Spark).
Proven track record of successfully delivering AI/ML projects and deploying models in a production environment.
Excellent problem-solving skills and the ability to work independently as well as in a team-based environment.
Strong communication and stakeholder management skills, with the ability to effectively present complex technical concepts to both technical and non-technical audiences.
Exposure to the insurance industry or financial services is a plus.