> Markdown version of [/jobs/ext/3973391-senior-data-scientist](https://www.wearedevelopers.com/jobs/ext/3973391-senior-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). --- # Senior Data Scientist - **Company:** FRACTAL LLC - **Location:** New York, NY, United States - **Experience:** Expert - **Salary:** $120,000.0 - $165,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Data Analysis, Microsoft Azure, Big Data, Cloud Computing, Cluster Analysis, Computer Programming, Information Engineering, Data Infrastructure, Data Transformation, Data Presentation, Distributed Computing Environment, Statistical Hypothesis Testing, Python (Programming Language), Machine Learning, NumPy, Object-Oriented Software Development, Recommender Systems, Power BI, Tensorflow, Azure Machine Learning, SQL Databases, Tableau (Software), Unstructured Data, Management of Software Versions, Supervised Learning, Google Cloud, Feature Engineering, Data Ingestion, Pytorch, Snowflake, Apache Spark, Deep Learning, Model Validation, Generative AI, Pandas, Microsoft Fabric, AI Platforms, Scikit Learn, Kubernetes, Information Technology, Xgboost, Feature Selection, Data Management, Machine Learning Operations, Stream Processing, Data Pipelines, Unsupervised Learning, Databricks - **Published:** October 27, 2026 - **Apply:** https://www.nettemps.com/us/en/W6EEF5E3989446CB4EC.ntap ## About the Role * MS or PhD in Computer Science, Data Science, Statistics, Mathematics, Engineering, Operations Research, or a related quantitative field. * 5+ years of applied machine learning, data science, or AI experience in a professional setting. * Demonstrated experience owning projects or major workstreams from initial problem definition through delivery. * Excellent programming skills in Python to include strong overall OOP experience. * Strong proficiency with machine learning and data science tools such as Scikit-learn, PyTorch, TensorFlow, pandas, NumPy, XGBoost, or similar frameworks. * Broad knowledge of machine learning and AI methods, including when to apply different approaches and what tradeoffs to consider. * Project experience in several of the following areas: supervised learning, unsupervised learning, time series forecasting, deep learning, operations research, optimization, anomaly detection, or Generative AI. * Familiarity with the machine learning lifecycle, including experimentation, versioning, deployment, monitoring, governance, and retraining. * Experience with production-oriented ML tools or workflow platforms such as MLflow, Airflow, Kubeflow, Databricks, or similar. * Familiarity with scalable data and AI technologies such as Spark, distributed processing, streaming systems, or cloud-based ML services. * Prior exposure to AWS, Azure, or Google Cloud, especially AI/ML services, is advantageous. * Ability to lead independently while collaborating effectively with client, product, engineering, and delivery teams. * Strong communication skills, including the ability to explain complex analytical work clearly to business stakeholders. * High ownership mindset, strong judgment, practical problem-solving ability, and a desire to create measurable business impact., * Hands-on experience with the C3 AI platform. * Experience working in an Embedded client environment, partner delivery model, enterprise SaaS implementation, or AI platform delivery role. * Experience delivering AI solutions for large enterprises or Fortune 500 clients. * Domain experience in manufacturing, energy, utilities, supply chain, aerospace, telecommunications, financial services, or other operationally complex industries. * Experience with demand forecasting, asset reliability planning, predictive maintenance, inventory optimization, or supply chain optimization. * Experience mentoring junior team members or leading small technical teams. ## Description We are seeking a highly motivated and analytical Senior Data Scientist with 4-6 years of experience in Machine Learning, Statistical Modeling, Predictive Analytics, and Data Science solutions. The ideal candidate will leverage advanced analytical techniques to extract insights from large and complex datasets, develop predictive models, and help drive data-driven decision-making across business functions. The role requires strong expertise in Python, SQL, machine learning algorithms, time-series forecasting, anomaly detection, and data storytelling. The candidate will work closely with business stakeholders, data engineers, product owners, and technology teams to solve critical operational and strategic challenges using data science methodologies. Experience with cloud and modern data platforms such as Databricks, Snowflake, Microsoft Fabric, and exposure to the C3 AI Platform will be highly preferred., Data Science & Analytics * Develop, implement, and maintain machine learning models for classification, regression, clustering, recommendation systems, and predictive analytics. * Design and execute advanced statistical analyses to identify business trends, risks, and opportunities. * Perform exploratory data analysis (EDA) to uncover patterns and generate actionable insights from structured and unstructured datasets. * Build forecasting models using time-series techniques for business planning, demand forecasting, asset performance prediction, and operational optimization. * Develop anomaly detection models to identify unusual patterns, operational failures, fraud indicators, or equipment performance issues. * Conduct root-cause analysis and hypothesis testing to support business decision-making. Machine Learning Model Development * Design and implement end-to-end machine learning pipelines from data ingestion to deployment. * Perform feature engineering, feature selection, and data transformation to improve model performance. * Evaluate models using appropriate validation techniques, performance metrics, and cross-validation methodologies. * Optimize machine learning algorithms for scalability, accuracy, and interpretability. * Monitor model performance and implement retraining strategies to ensure sustained effectiveness. Data Management & Engineering Collaboration * Partner with data engineering teams to build scalable data pipelines and analytical data models. * Work with large datasets using SQL, distributed computing frameworks, and cloud-based analytics platforms. * Ensure data quality, consistency, and governance standards are maintained throughout the analytics lifecycle. Business Engagement & Communication * Engage with business stakeholders to understand requirements, translate business problems into analytical solutions, and define success metrics. * Present analytical findings, model results, and recommendations to both technical and non-technical audiences. * Translate complex data science concepts into business-friendly insights and actionable recommendations. * Support strategic initiatives by providing data-driven forecasting and scenario analysis. Visualization & Reporting * Develop interactive dashboards and visualizations using Power BI, Tableau, or equivalent tools. * Communicate model outcomes and business insights through compelling visual storytelling and executive presentations.