Head of Data Science - Forsyth Barnes : Job Details

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This range is provided by Forsyth Barnes. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

$100.00/hr - $110.00/hr

Title: Head of Data Science

Location: New York

Rate: $110 p/h

Length: Contract

About the Role: As the Head of Data Science, you will be responsible for setting the vision and strategy for the data science team, leveraging advanced analytics, machine learning, and AI to deliver powerful insights and drive decision-making across the organization. You will collaborate closely with business leaders, technology teams, and data engineers to build sophisticated models that influence key financial services products and services.

Key Responsibilities:

• Lead and grow a high-performing data science team, driving collaboration, mentorship, and continuous learning.
• Develop and execute the data science strategy, ensuring alignment with the organization's objectives and customer needs.
• Use advanced statistical, machine learning, and AI techniques to generate actionable insights from large, complex datasets.
• Drive the development of predictive models, risk models, and algorithms that influence key business decisions and improve operational efficiency.
• Collaborate with engineering and IT teams to build scalable data infrastructure and implement data-driven solutions.
• Work closely with senior leadership to define and prioritize data science initiatives that align with business strategy.
• Establish and maintain best practices for data science, including model validation, A/B testing, and version control.
• Monitor emerging trends in data science, machine learning, and AI to keep the company at the forefront of innovation in financial services.
• Ensure compliance with regulatory standards and best practices in data handling, privacy, and security.

Key Qualifications:

• 8+ years of experience in data science, with at least 3+ years in a leadership role within financial services or fintech.
• Advanced proficiency in machine learning algorithms, predictive modeling, and statistical analysis.
• Strong experience with data manipulation and analysis tools such as Python, R, SQL, and frameworks like TensorFlow, PyTorch, or Scikit-learn.
• Expertise in working with large, complex datasets and experience in data wrangling, feature engineering, and data visualization.
• Proficiency in cloud platforms (AWS, GCP, or Azure) and experience building data pipelines in a distributed environment.
• Familiarity with Big Data technologies such as Hadoop, Spark, or Kafka.
• Deep understanding of financial services, including credit risk modeling, fraud detection, and quantitative analysis.
• Strong leadership experience, with the ability to inspire and guide cross-functional teams.
• Excellent communication skills with the ability to explain complex data science concepts to non-technical stakeholders.
• Master's or PhD in a relevant field (e.g., Computer Science, Statistics, Mathematics, Engineering, or Data Science).

If you're interested, please apply by emailing a copy of your most up to date CV and your current availability.