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Freelance Data Science Startup Jobs in New York (NOW HIRING)

... of a startup, we're hiring. SageSure, a leader in catastrophe-exposed property insurance, is ... In this role, you will lead a team of data scientists in solving some of the most complex and high ...

... of a startup, we're hiring. SageSure, a leader in catastrophe-exposed property insurance, is ... In this role, you will lead a team of data scientists in solving some of the most complex and high ...

... data science, applied analytics, or applied machine learning roles * Comfort operating as a senior IC in a fast-growing startup, balancing execution with technical judgment and prioritization

About the job Do you think like a management consultant, thrive in a startup environment, and can't ... The ideal candidate has a substantial Data Science and machine learning background with 8+ years of ...

About the job Do you think like a management consultant, thrive in a startup environment, and can't ... The ideal candidate has a substantial Data Science and machine learning background with 8+ years of ...

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Freelance Data Science Startup information

What is a freelance data science startup?

A Freelance Data Science Startup is a small business or entrepreneurial venture where individuals or small teams offer data science services independently, rather than working as full-time employees for a single company. These startups provide solutions such as data analysis, machine learning, predictive modeling, and data visualization to various clients on a project basis. Freelance data science startups often work with businesses that need expertise for specific projects or lack in-house data science resources. They may operate remotely and handle multiple clients simultaneously, allowing for flexibility and diverse experience. This model is popular among data scientists seeking autonomy and a variety of challenging projects.

What skills and qualifications are needed to thrive as a freelance data science startup founder?

To thrive as a Freelance Data Science Startup founder, you need strong expertise in data analysis, machine learning, programming (Python/R), and a solid educational background in statistics or computer science. Familiarity with tools like Jupyter, TensorFlow, cloud platforms (AWS, GCP), and data visualization software, as well as relevant certifications, is highly beneficial. Exceptional communication, client management, and entrepreneurial skills help differentiate successful founders in this space. These skills are crucial for delivering high-quality solutions, winning clients, and sustaining a competitive edge in the evolving data science market.

What unique challenges do freelance data scientists face when working with startups, and how can they manage them?

Freelance data scientists working with startups often encounter challenges such as rapidly changing project scopes, limited historical data, and the need to wear multiple hats. Since startups typically operate in fast-paced environments, priorities can shift quickly, requiring adaptability and strong communication skills. To manage these challenges, it's important to set clear expectations upfront, maintain transparent communication with stakeholders, and design flexible data solutions that can evolve as the business grows. Building strong relationships with both technical and non-technical team members can also help ensure project alignment and successful outcomes.

What is the difference between Freelance Data Science Startup vs Data Analyst?

AspectFreelance Data Science StartupData Analyst
CredentialsRelevant degrees, certifications in data science or analyticsDegree in statistics, data analysis, or related fields
Work EnvironmentIndependent, project-based, remote or on-siteTypically in corporate or organizational settings, often full-time
Employer & IndustrySelf-employed or startup clients across various industriesEmployers in finance, marketing, healthcare, etc.
Search & Comparison IntentLooking for freelance opportunities or startup roles in data scienceSeeking data analysis roles within organizations

Freelance Data Science Startups focus on independent, project-based work involving advanced data modeling and machine learning, often serving multiple clients. Data Analysts typically work within organizations analyzing data to inform business decisions. While both roles require analytical skills, freelance data science startups emphasize entrepreneurship and technical expertise, whereas data analysts focus on operational data insights within a company.

What are the most commonly searched types of Data Science Startup jobs in New York?

The most popular types of Data Science Startup jobs in New York are:

What cities in New York are hiring for Freelance Data Science Startup jobs?

Cities in New York with the most Freelance Data Science Startup job openings:

Director Data Science

SageSure

Jersey City, NJ

Full-time

Posted 17 days ago


Job description

Overview: 

If you're looking for the stability of a profitable, growing company with the entrepreneurial spirit of a startup, we're hiring. SageSure, a leader in catastrophe-exposed property insurance, is seeking a Director, Data Science. In this role, you will lead a team of data scientists in solving some of the most complex and high-impact challenges in the business. You will guide the development of advanced analytics, AI, and machine learning solutions while shaping strategy, influencing cross-functional decision-making, and building scalable processes that mature SageSure's data capabilities. 

We are looking for a highly motivated, strategically minded, and innovative leader who thrives in both ambiguity and complexity-someone who can elevate team performance, collaborate across the organization, and set a vision for the future of Data Science at SageSure. 

What you'd be doing: 

  • Partner with senior leaders across Product, Engineering, Program, and Operations to understand business needs and translate them into a cohesive Data Science strategy and roadmap. 
  • Influence and align stakeholders by articulating clear priorities, trade-offs, and expected outcomes; ensure downstream teams have full context to execute effectively. 
  • Foster a culture of accountability, collaboration, and continuous improvement across the team and cross-functional partners. 
  • Lead, mentor, and develop a high-performing team of data scientists; provide coaching, career development, and structured feedback while ensuring clarity of expectations. 
  • Build strong team health by promoting inclusion, psychological safety, and a values-driven culture. 
  • Ensure the team structure, processes, and operating rhythms support long-term scalability and organizational needs. 
  • Oversee the design, development, and deployment of machine learning models and advanced analytics solutions that drive business impact, improve operational efficiency, and strengthen decision-making. 
  • Champion experimentation, innovation, and responsible use of AI; ensure solutions adhere to best practices in model governance, data ethics, and performance monitoring. 
  • Translate complex technical concepts into clear, actionable insights for non-technical stakeholders, including senior executives. 
  • Build and refine scalable processes, documentation, and standards that enhance quality, reproducibility, and onboarding efficiency. 
  • Ensure responsible stewardship of data, models, and technical resources; make fiscally sound decisions aligned with departmental objectives and priorities. 
  • Break down silos by promoting cross-functional problem-solving and encouraging teams to think beyond their lane to achieve shared goals. 

We're looking for someone who has: 

  • Bachelor's or Master's degree in a quantitative field (Data Science, Computer Science, Statistics, Mathematics, etc.). 
  • 3+ years of leadership experience managing data scientists or analytics teams in a fast-paced environment. 
  • Deep expertise in Python, SQL, and modern data science/ML tooling (Pandas, NumPy, TensorFlow, etc.). 
  • Strong understanding of AWS or comparable cloud architecture. 
  • Demonstrated success delivering machine learning solutions that drive measurable business outcomes. 
  • Proven ability to think strategically, manage complex initiatives, and prioritize effectively across competing demands. 
  • Exceptional communication skills, with the ability to influence senior executives and guide teams through ambiguity. 

Highly preferred candidates also have: 

  • Experience in P&C insurance or another highly regulated, data-intensive industry. 
  • Exposure to large-scale, real-time data pipelines and MLOps practices. 
  • Experience building cross-functional operating models, processes, or governance frameworks. 
  • Experience leading through organizational change and building long-term analytics foundations. 

Data and AI at SageSure:  

At SageSure, data and AI aren't just functions-they're engines for innovation. Our Data & AI organization brings together Data Science, Business Intelligence, Data Management, and emerging AI capabilities to power smarter decisions and deliver meaningful impact across the business. From advanced machine learning models to scalable data ecosystems and real-time insights, we transform complex information into clarity that drives strategic outcomes. 

We're building a team of curious, collaborative problem-solvers who are excited about pushing the boundaries of what data and AI can do. Whether you're developing predictive models, enhancing AI-driven capabilities, strengthening data governance, or uncovering insights that influence key decisions, you'll play a critical role in shaping how SageSure uses data and intelligence to lead the future of insurance.Â