Data Scientist

Arkhya Tech Inc.; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Arkhya Tech Inc. is seeking a Data Scientist to advance Generative AI, LLMs, and conversational analytics from a remote LATAM-based team.

You will craft scalable data pipelines, design prompts for LLMs, and apply NLP techniques to extract actionable insights from large-scale conversational data. Ideal candidates bring 5+ years in data science, deep Python/SQL proficiency, and hands-on experience with prompt engineering, ETL/ELT workflows, and modern ML frameworks.

Qualifications

• Bachelor's degree in CS, Data Science, AI, ML, Statistics or related field, or equivalent practical experience.
• 5+ years of work experience in Data Science, ML, AI, NLP or analytics engineering.
• Hands-on experience with Prompt Engineering and Large Language Models (LLMs).
• Experience creating ETL/ELT pipelines for structured and unstructured data.
• Experience with conversational data and text analytics.
• Proficient in Python and SQL.
• Familiarity with Pandas, NumPy, Scikit-learn, SpaCy, TensorFlow, PyTorch, LangChain or LangGraph.

Responsibilities

• Develop ML, NLP and Generative AI solutions for conversational analytics and LLMs.
• Design, test and optimise prompts for Large Language Models using conversational datasets.
• Support prompt training and evaluation 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, summarisation, 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.

Skills

Python

SQL

NLP

Prompt engineering

Data pipelines

Education

Bachelor's degree in CS/Data Science/AI or related

MS degree (preferred) in CS/AI/ML/Data Science

Tools

Pandas

NumPy

Scikit-learn

SpaCy

TensorFlow

PyTorch

LangChain

LangGraph

Job description

Generative AI, LLM & Conversational Analytics

Location : Remote (LATAM)

The Team

Data Science at our organization brings together researchers, engineers and product teams to build adaptive, collaborative technologies focused on enabling action at all levels of an organization. This role will support Conversational Analytics and Generative AI initiatives by developing scalable data pipelines, prompt engineering approaches, sampling methodologies and Athena Studio workflows for large-scale conversational data.

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, summarisation, 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, summarisation, 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.