> Markdown version of [/jobs/ext/1104660-data-scientist](https://www.wearedevelopers.com/jobs/ext/1104660-data-scientist). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - **Company:** SolutionIT, Inc. - **Location:** Boston, MA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Mxnet, Agile Methodology, Amazon Web Services, Microsoft Azure, Big Data, Cloud Computing, Continuous Integration, IBM ILOG CPLEX Optimization Studio (CPLEX), Data Architecture, DevOps, Python (Programming Language), Machine Learning, Tensorflow, SQL Databases, Data Streaming, Google Cloud, Feature Engineering, Pytorch, Large Language Models, Apache Spark, Deep Learning, Model Validation, Scikit Learn, Xgboost, Machine Learning Operations - **Published:** June 10, 2026 - **Apply:** https://www.dice.com/job-detail/5562eb1e-d718-4fb2-88a6-4bc113520e26 ## About the Role * Expertise in operations research modeling (LP, IP, MIP) and tools (CPLEX, Gurobi, etc). * Expertise in building machine learning models, including supervised, unsupervised, and deep learning methods * Expertise in feature engineering, model evaluation, and hyperparameter tuning. * Expertise in Python, SQL, and Spark, and a broad array of machine learning frameworks (Scikit-Learn, XGBoost, TensorFlow, PyTorch, MXNet, LLM, etc). * Experience in developing and deploying solutions in a Cloud environment (AWS, Azure, Google Cloud Platform) with large datasets. * Experience with streaming data architectures. * Experience operating in an Agile Methodology environment. * Experience with DevOps and CI/CD concepts. PREFERRED SKILLS: * Exposure to hospitality, travel, or service industry data and optimization use cases. * Strong understanding of data architecture and MLOps best practices. * Proven ability to translate complex analytics into business impact. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [TikTok's Privacy Innovation](https://www.wearedevelopers.com/videos/1036-tiktok-s-privacy-innovation) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Explainable machine learning explained](https://www.wearedevelopers.com/videos/589-explainable-machine-learning-explained) - [DevOps Maturity Check – a way to balance autonomy and alignment](https://www.wearedevelopers.com/videos/58-devops-maturity-check-a-way-to-balance-autonomy-and-alignment) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) ## Related Articles - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Everything a Developer Needs to Know About MCP with Neo4j](https://www.wearedevelopers.com/magazine/604-everything-a-developer-needs-to-know-about-mcp-with-neo4j) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)