MEAN Developer IRC

Description

We are seeking a highly skilled Data Scientist with expertise in Natural Language Processing (NLP), Large Language Models (LLMs), and deep learning to join our team. The ideal candidate will have hands‑on experience with AWS cloud services and a strong background in developing and deploying advanced text analytics solutions. Experience with data engineering concepts and tools is a significant advantage.

Global Logic estimates the starting pay range for this role to be performed in San Antonio is $150,000 -$160,000 and reflects base salary only. This pay range is provided as a good faith estimate and the amount offered may be higher or lower. Global Logic takes many factors into consideration in making an offer, including candidate qualifications, work experience, operational needs, travel and onsite requirements, internal peer equity, prevailing wage, responsibilities, and other market and business considerations.

• Strong programming skills in Python (Pandas, Num Py, scikit‑learn, PyTorch, Tensor Flow, Hugging Face Transformers).
• Experience with AWS cloud services for data science and machine learning.
• Expertise in NLP techniques: text classification, sentiment analysis, entity recognition, topic modelling, summarisation, etc.
• Hands‑on experience with LLMs and deep learning architectures for text data.
• Familiarity with data scripting, ETL, and automation for large‑scale text processing.
• Knowledge of the latest algorithms and research in NLP and deep learning.
• Excellent problem‑solving, communication, and teamwork skills.
• Experience with MLOps, model deployment, and monitoring on cloud platforms.

• Experience with data engineering concepts such as ETL pipeline development, data modelling, and data warehousing.
• Familiarity with tools like Apache Spark, AWS Glue, or similar data processing frameworks.
• Knowledge of data orchestration and workflow management tools (e.g., Airflow, Step Functions).
• Experience in optimizing data storage and retrieval for large‑scale analytics.

• Design, develop, and deploy NLP and text analytics solutions using state‑of‑the‑art algorithms and deep learning techniques.
• Work with Large Language Models (LLMs) such as GPT, BERT, or similar architectures for various text processing tasks.
• Build and optimise data pipelines and workflows on AWS (e.g., S3, Lambda, Sage Maker, Glue, EMR).
• Perform data wrangling, cleaning, and scripting for large‑scale unstructured text datasets.
• Research and implement the latest advancements in NLP, and deep learning.
• Collaborate with cross‑functional teams to understand business requirements and deliver actionable insights.
• Monitor, evaluate, and improve model performance using appropriate metrics and validation techniques.

Culture of caring. At Global Logic, we prioritise a culture of caring. Across every region and department, at every level, we consistently put people first. From day one, you’ll experience an inclusive culture of acceptance and belonging, where you’ll have the chance to build meaningful connections with collaborative teammates, supportive managers, and compassionate leaders.

Learning and development. We are committed to your continuous learning and development. You’ll learn and grow daily in an environment with many opportunities to try new things, sharpen your skills, and advance your career h our Career Navigator tool as just one example, Global Logic offers a rich array of programmes, training curricula, and hands‑on opportunities to grow personally and professionally.

Interesting & meaningful work. Global Logic is known for engineering impact for and with clients around the world. As part of our team, you’ll have the chance to work on projects that matter. Each is a unique opportunity to engage your curiosity and creative problem‑solving skills as you help clients reimagine what’s possible and bring new solutions to market. In the process, you’ll have the privilege of working on some of the most cutting‑edge and impactful solutions shaping the world today.

Balance and flexibility. We believe in…