Data Scientist (Generative AI, LLM & Conversational Analytics)

We are seeking a Data Scientist to support Conversational Analytics and Generative AI initiatives through the development of scalable data pipelines, prompt engineering approaches, sampling methodologies, and Athena Studio workflows for large-scale conversational data. This role will collaborate closely with Data Science, Engineering, and Product teams to analyze conversational datasets, drive AI-powered insights, and help build adaptive technologies that enable action across the organization. Location : Remote, Mexico only . About Us: Abstra is a fast-growing, Nearshore Tech Talent services company, providing top Latin American tech talent to U.S. companies and beyond. Founded by U.S.-bred engineers with over 15 years of experience, Abstra specializes in sourcing skilled professionals across a wide range of technologies to meet our clients’ needs, driving innovation and efficiency. Responsibilities: As a Data Scientist on the Data Science team, you will develop machine learning, NLP and Generative AI solutions focused on conversational analytics and large language models. Design, develop, test and optimise prompts for Large Language Models (LLMs) using conversational datasets. Support prompt training and evaluation activities to improve accuracy, relevance and consistency of AI-driven outputs. Create scalable data pipelines for ingestion, transformation, sampling and processing of conversational and unstructured text data. Develop sampling methodologies for high-volume conversational datasets, including sampling within conversations and across conversations. Prepare and process conversational data for use in Athena Studio and related analytics workflows. Apply NLP and machine learning techniques for text understanding, classification, summarization, pattern recognition and conversational insights. Run data science analyses and experiments independently while collaborating with engineering, analytics and product teams. Communicate technical methods, results and recommendations clearly to both technical and non-technical stakeholders. Minimum Qualifications Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Statistics, Mathematics or related technical discipline, or equivalent practical experience. 5+ years of relevant work experience in Data Science, Machine Learning, Artificial Intelligence, NLP or analytics engineering. Hands-on experience with Prompt Engineering and Large Language Models (LLMs). Experience creating data pipelines, ETL/ELT workflows or data processing pipelines for structured and unstructured datasets. Experience working with conversational data, text analytics, customer interaction data or other large-scale unstructured data sources. Demonstrated proficiency in Python and SQL. Working knowledge of packages and frameworks associated with data wrangling, analysis and machine learning, such as Pandas, NumPy, Scikit-learn, SpaCy, TensorFlow, PyTorch, LangChain or LangGraph. Preferred Qualifications MS degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science or related technical discipline. Experience using Athena Studio and AWS Athena for analytics or data processing workflows. Experience with prompt training, prompt evaluation, LLM evaluation frameworks or fine-tuning concepts. Experience in one or more of the following areas: Natural Language Processing for text understanding, classification, summarization, recommendation/ranking systems or conversational analytics. Experience with cloud data and machine learning platforms such as AWS S3, AWS Glue, SageMaker, Databricks, Vertex AI or Kubeflow. Experience with embeddings, semantic search, vector databases, RAG patterns or representation learning for unstructured data. Strong communication skills, especially in describing technical methods and results to both technical and non-technical audiences. Ability to collaborate effectively with geographically distributed teams across near-shore and offshore locations. What We Offer: Flexible working hours and hybrid/remote work options. Opportunities for professional growth and development. A collaborative and inclusive work environment. The chance to work on impactful projects with a talented team. Excellent compensation in USD. Hardware and software setup (mandatory). Pre-Employment Verification As part of our standard onboarding process, candidates who successfully complete the interview process and accept an employment offer will be required to complete an employment verification check, and background check. This process will confirm job titles and dates of employment with two previous employers and is a standard requirement for all new employees joining the company.