Data Scientist

Role Overview

Join Orange Business as a Data Scientist, a key role in managing and delivering assigned projects while leveraging machine learning and statistics to solve complex business problems. You will be deeply involved in the entire LLM development lifecycle, from data preparation to deployment, and collaborate across product, technical, and support teams.

Responsibilities

• Manage and deliver all assigned projects as per agreed time frame, allocated budget, resource and quality criteria.
• Managing project risks, including the development of contingency plans.
• Responsible for Identification & all the communication with the stakeholders.
• Work with product, Technical and Customer Support on identifying problems in different areas where machine learning/statistics can help.
• Present your findings to both technical and non-technical audiences.
• Participate in the entire LLM development lifecycle, from problem definition and data preparation to model training, evaluation, and deployment.
• Design and implement novel LLM architectures and training techniques, leveraging deep learning frameworks like TensorFlow and PyTorch.
• Develop and maintain efficient pipelines for data preprocessing, training, and inference.
• Collaborate with data scientists to curate, clean, and prepare high-quality training data for LLMs.
• Evaluate LLM performance using appropriate metrics and identify opportunities for improvement.
• Apply advanced machine learning algorithms, statistical methods and predictive modeling techniques on large and varied data sets that include application logfiles, other online application telemetry, structured and unstructured data sources.
• Deploy LLMs to production environments and monitor their performance for accuracy, fairness, and efficiency.
• Design and develop front-end interfaces for AI-powered applications using modern web technologies such as HTML, CSS, JavaScript, and frameworks like React or Angular.
• Stay up-to-date on the latest advancements in LLM research and identify opportunities to incorporate them into your work.
• Build scalable back-end systems and APIs to support AI model integration and data processing using languages such as Python, Java, or Node.js.
• Collaborate with researchers to explore new applications for LLMs in various domains.
• Manage the infrastructure needed for data scientists to run their experiments and deploy models. This includes setting up compute clusters with GPUs or TPUs for computationally intensive tasks, configuring cloud storage for datasets, and managing containerized environments for model deployment.
• Document your work clearly and concisely, including research papers, technical reports, and code documentation.

Requirements

• Have extensive experience of the design and delivery of AI or Big Data solutions.
• Hands-on applied research experience developing and implementing machine learning models on large scale data sets.
• Expertise in machine learning and statistical analysis approaches such as classification, clustering, regression, statistical inference, collaborative filtering, natural language processing.
• Hands-on experience in conducting analyses on unstructured structured / semi-structured data.
• Ability to drive initiatives from within the team and realize them for organization and/or team’s benefit.
• Excellent interpersonal and communication skills.
• You bring rigor, passion for challenges, and determination. You seek the opportunity to expand your expertise, achieve your goals, and thrive.