Lead Data Scientist

SUMMARY:
A global systems integrator and digital transformation expert focused on technology-enabled CX are seeking a talented Lead Data Scientist to join their dynamic team and help drive the expansion of their innovative data analytics offering.

As the Lead Data Scientist at the Company, you will be responsible for developing and implementing advanced analytics solutions tailored to the needs of clients in the contact centre industry.

You will have the opportunity to work on a diverse range of projects across a varied client base. You will work as part of the broader CX Automation team, which specialises in designing, building and deploying AI powered chatbot and voice automations. The data science function leverages cutting-edge technology to derive data-driven insights that offer huge benefits to our customers, fueling our demand for automation capabilities. The role will involve prioritising and delegating data science work within the team. The Lead Data Scientist will also be expected to provide thought leadership and shape the future of the Company’s analysis offerings.

POSITION INFO:
Key Interfaces:
- Conversational Design Team
- CX Development Team
- CX Development Manager
- CX Automation Practice Lead
- 3rd Parties as appropriate, including customer technical and business representatives
- Innovations Team
- Presales Team

Key Competencies :
- Problem-Solving Skills: Excellent analytical and problem-solving skills with a keen attention to detail.
- Python Proficiency: Strong knowledge of Python and standard machine learning libraries.
- AWS Experience: Strong experience working with AWS, including deploying and managing machine learning solutions in the cloud.
- Source Management and Repositories: Experience with version control systems (e.g., Git) and familiarity with modern software development workflows.
- Full Software Lifecycle: Experience designing machine learning models from scratch and seeing them through the full software lifecycle, from concept and development to post-deployment monitoring and optimisation.
- Statistical Expertise: Solid understanding of statistical concepts and techniques, with a demonstrated ability to apply them in machine learning applications.
- Communication: Strong communication and interpersonal skills, with the ability to collaborate effectively in a team environment.

Preferred Competencies:
- Contact Centre Experience: Experience working within the contact centre industry, applying machine learning to real-world challenges.
- NLP and Text Analytics: Experience with natural language processing and text analytics, particularly in domain-specific applications.
- Cloud Platforms: Familiarity with cloud computing platforms, including AWS (preferred), Azure, or Google Cloud.
- Data Visualization: Proficiency with data visualization tools such as Amazon QuickSight, Power BI, or Tableau.
- Prompt Engineering: Experience in prompt engineering for large language models (e.g., GPT, Claude, Gemini).
- LLM Frameworks: Familiarity with frameworks such as LangChain or Amazon Bedrock for deploying and integrating large language models.
- Specific Python Libraries: e.g. scikit-learn, pandas, NumPy, TensorFlow, PyTorch.
- Docker: Familiarity with containerization technologies like Docker, Docker Compose, and Docker Swarm is a plus. Experience using these tools to build, deploy, and scale data science applications is highly desirable.

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