Data Scientist (Remote - US)

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Data Scientist in the United States.

This role offers the opportunity to design, develop, and deploy advanced data science and machine learning solutions, including working with large language models (LLMs) on cloud-based platforms. You will work in a collaborative environment with data engineers, cloud architects, and business stakeholders to ensure ML models are effectively integrated into production workflows. The position emphasizes hands-on experience with Databricks on Azure, PySpark for distributed data processing, and LLM fine-tuning. You will analyze complex datasets, implement scalable solutions, and contribute to cutting-edge AI projects. The role allows you to directly impact the organization’s data-driven decision-making and innovation while staying at the forefront of AI/ML developments.

Accountabilities

• Design, develop, and deploy end-to-end machine learning and data science solutions in a cloud environment (Databricks on Azure).
• Prepare and process large-scale datasets using PySpark for cleaning, transformation, and feature engineering.
• Apply fine-tuning, optimization, and deployment of large language models for domain-specific applications.
• Conduct exploratory data analysis, statistical modeling, and hypothesis testing to generate actionable insights.
• Collaborate with data engineers, cloud architects, and business stakeholders to ensure seamless integration of ML models into production workflows.
• Document methodologies, experiments, and best practices to facilitate knowledge sharing and reproducibility.
• Stay updated on advancements in AI, ML, LLMs, and cloud technologies to implement innovative solutions.

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, AI/ML, or a related field.
• Proven experience as a Data Scientist with strong exposure to ML and NLP projects.
• Hands-on experience with Databricks on Azure, including MLflow, Delta Lake, and Databricks ML.
• Proficiency in PySpark for distributed large-scale data processing.
• Experience training, fine-tuning, and deploying LLMs within Databricks.
• Strong programming skills in Python and familiarity with ML frameworks (TensorFlow, PyTorch, Scikit-learn, Hugging Face).
• Solid understanding of data science workflows: data wrangling, feature engineering, model development, and evaluation.
• Working knowledge of Azure cloud services (Azure Data Lake, Azure Synapse, Azure ML).
• Strong analytical thinking, problem-solving, and communication skills.
• Good-to-have: experience with MLOps, CI/CD for ML, vector databases, prompt engineering, and RAG techniques.