Data Scientist
Remote / Online - Candidates ideally in
Boise, Ada County, Idaho, 83701, USA
Listed on 2026-11-01
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
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.
- 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.
- 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.
- 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
- 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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