Sr. Data Scientist

Organisational Context:

Company Name: CIMET

CIMET - A Comparison Software Leader

Website: www.cimet.com.au

Product Link: https://www.econnex.com.au

LinkedIn: https://www.linkedin.com/company/cimet/about

CIMET provides end-to-end comparison and signup of energy, telecommunication, credit cards and other product plans through its online solution in a B2B and B2C environment. It presently caters to more than 40+ Utilities and Financial Service providers and has over 200+ partners. The online comparison market is extremely crowded in Australia, with most comparators providing a light touch directory solution. CIMET saw this as an opportunity and developed a fully integrated online comparison and signup platform.

On 15 March 2022, CIMET partnered with iSelect who acquired a 49% stake in CIMET Holdings.

Going forward, CIMET will use this investment from iSelect to expand into new products including Credit Cards, Home loans, Car loans, Personal loans, Life Insurance, Health Insurance, Pet Insurance among others. CIMET today has around 200+ team members, across Australia, India and Philippines and will double over the next 2 years.

We are looking for a highly experienced Senior Data Scientist with a deep understanding of AI/ML technologies, including Recommendation Systems, Chatbots, Generative AI, and Large Language Models (LLMs). The ideal candidate will have hands-on experience in applying these technologies to solve real-world problems, working with large datasets, and collaborating with cross-functional teams to deliver innovative data-driven solutions.

Key Responsibilities:

• Design, develop, and optimize recommendation systems to enhance user experience and engagement across platforms.
• Build and deploy chatbots with advanced NLP capabilities for automating customer interactions and improving business processes.
• Lead the development of Generative AI solutions, including content generation and automation.
• Research and apply Large Language Models (LLMs) like GPT, BERT, and others to solve business-specific problems and create innovative solutions.
• Collaborate with engineering teams to integrate machine learning models into production systems, ensuring scalability and reliability.
• Perform data exploration, analysis, and feature engineering to improve model performance.
• Stay updated on the latest advancements in AI and ML technologies, proposing new techniques and tools to enhance our product capabilities.
• Mentor junior data scientists and engineers, providing guidance on best practices in AI/ML model development and deployment.
• Collaborate with product managers and business stakeholders to translate business goals into AI-driven solutions.
• Work on model interpretability, explainability, and ensure models are built in an ethical and responsible manner.

Required Skills And Qualifications:

• 5+ years of experience in data science or machine learning, with a focus on building and deploying AI models.
• Strong expertise in designing and developing recommendation systems and working with collaborative filtering, matrix factorization, and content-based filtering techniques.
• Hands-on experience with chatbots using Natural Language Processing (NLP) and conversational AI frameworks.
• In-depth understanding of Generative AI, including transformer-based models and GANs (Generative Adversarial Networks).
• Experience working with Large Language Models (LLMs) such as GPT, BERT, T5, etc.
• Proficiency in machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• Strong programming skills in Python and libraries such as NumPy, Pandas, Hugging Face, and NLTK.
• Experience with cloud platforms like AWS, GCP, or Azure for deploying and scaling machine learning models.
• Solid understanding of data pipelines, ETL processes, and working with large datasets using SQL or NoSQL databases.
• Knowledge of MLOps and experience deploying models in production environments.
• Strong problem-solving skills and a deep understanding of statistical methods and algorithms.

Preferred Qualifications:

• Experience with Reinforcement Learning and Recommender Systems personalization techniques.
• Familiarity with ethical AI and model bias mitigation techniques.
• Experience with A/B testing, experimentation, and performance tracking for AI models in production.
• Prior experience mentoring junior data scientists and leading AI/ML projects.
• Strong communication and collaboration skills, with the ability to convey complex technical concepts to non-technical stakeholders.

Challenges Of The Position: