Data Scientist

Remote (USA) contract role for a Data Scientist focused on predictive analytics, machine learning, neural networks, and practical GenAI/LLM solutions.

Responsibilities

• Analyze large and complex datasets to uncover patterns, trends, and business opportunities.
• Develop, optimize, and deploy machine learning models for business and operational use cases.
• Design and implement neural-network and deep-learning solutions when appropriate.
• Perform feature engineering, data preprocessing, model training, and validation.
• Evaluate models using suitable statistical and machine-learning metrics.
• Run experiments with different algorithms and architectures to improve model performance.
• Partner with data engineers to build reliable datasets and scalable data pipelines.
• Create proof-of-concepts using LLMs and Generative AI for selected business scenarios.
• Build or contribute to RAG, embeddings, vector search, and prompt-engineering solutions.
• Collaborate with software engineering teams to productionize machine-learning models.
• Monitor model performance and recommend improvements or retraining strategies.
• Share analytical findings, model results, and recommendations with technical and business stakeholders.

Requirements

• 5+ years of experience in Data Science, Machine Learning, or Applied AI.
• Strong programming skills in Python and common data science libraries.
• Hands-on experience building and deploying ML models for classification, regression, clustering, forecasting, or recommendation use cases.
• Strong understanding of supervised and unsupervised learning, including feature engineering, model selection, validation, and performance evaluation.
• Practical experience with neural networks and deep learning.
• Experience with frameworks such as PyTorch, TensorFlow, or Keras.
• Knowledge of neural network architectures including CNNs, RNNs/LSTMs, Transformers, or similar approaches.
• Experience with NLP, text analytics, or unstructured data is highly desirable.
• Some hands-on experience with Generative AI / LLMs, including prompt engineering, embeddings, vector search, RAG, or LLM-based applications.
• Familiarity with GenAI platforms such as OpenAI, Azure OpenAI, AWS Bedrock, Google Vertex AI, or comparable services is a plus.
• Experience with SQL and working with structured and unstructured datasets.
• Experience with Pandas, NumPy, Scikit-learn, Matplotlib/Seaborn, or equivalent tooling.
• Understanding of model evaluation, hyperparameter tuning, cross-validation, and model explainability.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Familiarity with ML pipelines, MLOps, model deployment, and monitoring.
• Ability to translate business problems into measurable ML and data science solutions.

Preferred Qualifications

• Master’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
• Experience with Transformers, LLMs, NLP, RAG, embeddings, or vector databases.
• Experience with Databricks, Spark, Snowflake, AWS, Azure, or GCP.
• Familiarity with Docker, Kubernetes, MLflow, Airflow, or CI/CD.
• Experience taking machine-learning models from prototype to production.
• Experience in enterprise environments such as financial services, retail, healthcare, technology, or manufacturing.

Technical Stack

• Languages: Python, SQL
• Machine Learning: Scikit-learn, XGBoost, LightGBM
• Deep Learning: PyTorch, TensorFlow, Keras
• Neural Network Architectures: CNNs, RNNs/LSTMs, Transformers
• AI/GenAI: LLMs, prompt engineering, RAG, embeddings, vector search, Transformers
• Data: Pandas, NumPy, Spark, Databricks, Snowflake
• Cloud: AWS, Azure, GCP
• MLOps: MLflow, Docker, Kubernetes, CI/CD
• Visualization: Power BI, Tableau, Matplotlib, Seaborn

Additional Details

• Location: Remote (remote), USA
• Job type: Contract
• Duration: 12+ Months Contract
• Experience range: 5-10 Years
• Core focus: Hands-on experience with traditional machine learning and neural networks, plus practical exposure to GenAI/LLMs