Forsyth Barnes
Data Scientist (Ref: 191582)
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is a Data Scientist position in New York City for a contract duration, offering a competitive pay rate. Requires 5+ years of experience in data science, expertise in PyTorch and Databricks, and strong knowledge of Reinforcement Learning fundamentals.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
October 8, 2025
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
New York, United States
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🧠 - Skills detailed
#Batch #Spark (Apache Spark) #Data Science #MLflow #Pandas #PyTorch #AI (Artificial Intelligence) #Scala #Reinforcement Learning #Data Processing #Data Pipeline #Programming #Python #ML (Machine Learning) #Databricks #Libraries #NumPy
Role description
💼 Job Title: Data Scientist
💰 Industry: Fintech
📍 Location: New York City
🕒 Contract: Contract
We’re partnering with an exciting Fintech organisation driving innovation through intelligent decision systems. They are developing a next-generation Next Best Action platform powered by Reinforcement Learning (RL), PyTorch, and Databricks. They’re seeking a skilled Data Scientist who can design, build, and deploy reinforcement learning models that continuously optimize customer interactions and strategic decision-making.
🧾 Key Responsibilities:
• Design and implement reinforcement learning algorithms (e.g., policy gradient, DQN, actor-critic) using PyTorch.
• Build, train, and evaluate RL models on Databricks, leveraging distributed data processing and MLflow for experiment tracking.
• Define and operationalize Next Best Action strategies by modeling reward functions and decision policies aligned with business outcomes.
• Develop and maintain scalable data pipelines and feature stores to support both real-time and batch decisioning.
🧾 Skills & Experience:
• 5+ years of experience in data science, applied ML, or AI engineering.
• Hands-on experience developing and deploying models in PyTorch.
• Strong knowledge of Reinforcement Learning fundamentals — exploration vs. exploitation, reward design, and policy/value methods.
• Proficiency in Databricks, including Spark-based data processing and model lifecycle management.
• Solid programming experience in Python and libraries such as NumPy, pandas, and scikit-learn.
💼 Job Title: Data Scientist
💰 Industry: Fintech
📍 Location: New York City
🕒 Contract: Contract
We’re partnering with an exciting Fintech organisation driving innovation through intelligent decision systems. They are developing a next-generation Next Best Action platform powered by Reinforcement Learning (RL), PyTorch, and Databricks. They’re seeking a skilled Data Scientist who can design, build, and deploy reinforcement learning models that continuously optimize customer interactions and strategic decision-making.
🧾 Key Responsibilities:
• Design and implement reinforcement learning algorithms (e.g., policy gradient, DQN, actor-critic) using PyTorch.
• Build, train, and evaluate RL models on Databricks, leveraging distributed data processing and MLflow for experiment tracking.
• Define and operationalize Next Best Action strategies by modeling reward functions and decision policies aligned with business outcomes.
• Develop and maintain scalable data pipelines and feature stores to support both real-time and batch decisioning.
🧾 Skills & Experience:
• 5+ years of experience in data science, applied ML, or AI engineering.
• Hands-on experience developing and deploying models in PyTorch.
• Strong knowledge of Reinforcement Learning fundamentals — exploration vs. exploitation, reward design, and policy/value methods.
• Proficiency in Databricks, including Spark-based data processing and model lifecycle management.
• Solid programming experience in Python and libraries such as NumPy, pandas, and scikit-learn.
