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Data Scientist

Remote / Online - Candidates ideally in
Boise, Ada County, Idaho, 83701, USA
Listing for: Solutions Sync
Remote/Work from Home position
Listed on 2026-11-01
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, AI Engineer (Applied/Software), Data Scientist
Salary/Wage Range or Industry Benchmark: 124000 - 193000 USD Yearly USD 124000.00 193000.00 YEAR
Job Description & How to Apply Below

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 product ionize 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 Py Torch ,
    Tensor Flow
    , 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
    , Num Py
    , 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, Tensor Flow, Keras
  • Neural Network Architectures: CNNs, RNNs/LSTMs, Transformers
  • AI/GenAI: LLMs, prompt engineering, RAG, embeddings, vector search, Transformers
  • Data: Pandas, Num Py, 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
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