Lead Data Scientist - Machine Learning (5-9 yrs)

Summary :

A highly skilled and experienced Lead Data Scientist specializing in text data analysis and be responsible for driving innovative solutions using advanced analytics techniques to process, analyze, and extract valuable insights, and provide actionable recommendations to improve business performance.

Responsibilities :

- Collaborate with cross-functional teams and stakeholders to identify business requirements and objectives, manage deliverables against timelines, present of results and implement the model.

- Utilize advanced statistical analysis techniques to perform hypothesis testing, A/B testing, and predictive modeling.

- Stay abreast of the developments in the rapidly changing field of AI and machine learning.

- Mentor and coach junior team members and provide support on projects requiring advanced skill and domain expertise.

- Gain deeper understanding of Chubb's business and develop expertise on multiple lines of business.

- Use broad spectrum of NLP, Machine Learning, and deep learning techniques to extract impactful features from unstructured data.

- Develop and implement models that help with drawing risk related insights from large datasets to aid business decision making; Ensure that the model can meet the desired KPIs postproduction.

- Develop metrics to measure business performance and monitor the effectiveness of data-driven initiatives.

- Collaborate with IT teams to optimize data collection, storage, and retrieval processes to support efficient and reliable data analytics.

Requirements :

- Sound understanding of Generative AI based models and Prompt Engineering and LLMs to drive innovation and generate valuable insights from the data.

- Strong grasp of foundational ML concepts, including Probabilistic Models, Supervised vs Unsupervised Learning, Ensemble Techniques, Hyperparameter Optimization, and Deep Learning.

- Good knowledge in machine learning tools and libraries (matplotlib, ggplot, scikit-learn, h2o, MLlib, etc.)

- Proficient in Python with strong capabilities in data engineering, data transformation, data analysis and data dashboard building. Knowledge of R/SQL would be an add-on.

- Strong understanding of BERT and Transformers models is highly desired for this position.

- Bachelor's degree in computer science, Statistics, Math, Actuarial, or related quantitative fields. Advanced degree in data science, business analytics would be an add on.

- Minimum 6 years of hands-on experience in data analytics fields would be good.

- Previous exposure to/ knowledge of the insurance industry will be an added advantage.

- A deep passion for staying up to date with the latest advances and trends in the fields of ML, AI, and data science.