Central Point Partners

Data Scientist

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data Scientist with a contract length of "unknown," offering a pay rate of "unknown." Key skills include machine learning, predictive modeling, and experience with R, Python, and cloud technologies. A Master's degree and financial services background are preferred.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
February 20, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Columbus, OH
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🧠 - Skills detailed
#AWS (Amazon Web Services) #Visualization #Data Analysis #Big Data #Web Scraping #Computer Science #Deep Learning #"ETL (Extract #Transform #Load)" #Scala #Scripting #AWS SageMaker #Statistics #ML (Machine Learning) #R #Data Pipeline #Linear Regression #SQL (Structured Query Language) #Leadership #AI (Artificial Intelligence) #Python #NoSQL #Data Science #SageMaker #Regression #TensorFlow #Predictive Modeling #Cloud #SAS
Role description
Overview: Our client's Enterprise Data and Analytics team is growing, and we're looking for an outstanding Senior Data Scientist to join our team. You will leverage machine learning, segmentation, and statistical inference on huge data sets to improve how they understand our client's customers and the communities they serve. As we advance our data science and analytics capabilities, we want experts in modeling complex business problems and discovering business insights using statistical, algorithmic, mining, and visualization techniques. The Senior Data Scientist contributes to building and developing the organization's data infrastructure and supports the senior leadership with insights, management reports, and analysis for decision-making processes. Responsibilities: • Performs advanced analytics methods to extract value from business data • Performs large-scale experimentation and build data-driven models to answer business questions • Conducts research on cutting-edge techniques and tools in machine learning/deep learning/artificial intelligence • Determines requirements that will be used to train and evolve deep learning models and algorithms • Articulates a vision and roadmap for the exploitation of data as a valued corporate asset • Influences product teams through presentation of data-based recommendations • Evangelizes best practices to analytics and products teams • Owns the entire model development process, from identifying the business requirements, data sourcing, model fitting, presenting results, and production scoring Skills: • Up-to-date knowledge of machine learning and data analytics tools and techniques • Strong knowledge in predictive modeling methodology • Experienced at leveraging both structured and unstructured data sources • Willingness and ability to learn new technologies on the job • Demonstrated ability to communicate complex results to technical and non-technical audiences • Demonstrated ability to work effectively in teams as well as independently across multiple tasks while meeting aggressive timelines • Strategic, intellectually curious thinker with focus on outcomes • Professional image with the ability to form relationships across functions • Strong experience with R/RStudio, Python, SAS, SQL, NoSQL • Strong experience with Cloud Machine Learning technologies (e.g., AWS Sagemaker) • Strong experience with machine learning environments (e.g., TensorFlow, scikit-learn, caret) • Strong understanding of statistical methods and skills such as Bayesian Networks Inference, linear and non-linear regression, hierarchical, mixed models/multi-level modeling • Financial Services background preferred Experience: • 1-3 years' work and/or educational experience in machine learning or cloud computing, experience using statistics and machine learning to solve complex business problems, experience conducting statistical analysis with advanced statistical software, experience scripting languages, and packages, experience building and deploying predictive models, experience web scraping, and scalable data pipelines and experience with big data analysis tools and techniques. Education: • Master's degree in computer science, statistics, economics or related fields