Senior Data Scientist

Senior Data Scientist Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets. An ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite is the one who empowers imagination with intelligence. Fractal has been featured as a Great Place to Work by The Economic Times in partnership with the Great Place to Work® Institute and recognized as a 'Cool Vendor' and a 'Vendor to Watch' by Gartner. Please visit Fractal | Intelligence for Imagination for more information about Fractal

Location:
New York City, NY (On-site) Note: This position is not eligible for Immigration Sponsorship at this time. Position Overview: 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.

Key Responsibilities
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.

Qualifications:
* 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 approach