Remote Data Science Engineer Jobs in New York City

Discover an Impactful Remote Data Role Based in NYC

Do you thrive in an environment where data shapes direction, and innovation is the language of success? Are you ready to work remotely while driving the future of data engineering in one of the most dynamic cities in the world? We seek a Remote Data Science Engineer passionate about scalable systems, machine learning architecture, and real-time insights. This fully remote role based in New York City offers flexibility, challenge, and impact.

The Importance of This Position in Our Data-Driven Strategy

Data is more than numbers—it's the engine of decision-making and growth. Our systems handle an immense volume of real-time information daily to enhance customer experiences, optimize operational efficiency, and drive predictive decision models. As a key member of our data science engineering team, you will be entrusted with building, optimizing, and scaling systems that empower real-time data intelligence across departments.

We are proud to be part of a company where innovation isn't an option—it's a core value. We’ve reduced query latency by 34%, increased model deployment frequency by 50%, and achieved 98.6% data pipeline uptime. You’ll have a chance not just to build systems, but shape how data science is practiced in a modern, remote-first organization.

Key Responsibilities of the Remote Data Science Engineer

Data Architecture and Engineering

• Design and maintain robust data pipelines and APIs that process structured and unstructured data from diverse sources
• Build scalable data lakes and warehouses optimized for fast retrieval and real-time analytics.
• Implement ETL frameworks that support reproducibility, performance, and fault tolerance.

Model Development and Integration

• Collaborate with data scientists to transform prototype models into production-level machine learning applications.
• Design batch and streaming services to integrate model outputs into business workflows
• Deploy models using CI/CD best methodologies with Docker, Airflow, and Kubernetes.

Collaborative Development Across Teams

• Partner with product, analytics, and infrastructure teams to co-develop data solutions that scale across products
• Translate business needs into measurable engineering deliverables
• Mentor junior engineers, contribute to technical documentation, and lead code reviews

Remote Work Culture and Engineering Environment

We believe best work emerges from environments built on trust, purpose, and autonomy. You’ll collaborate with a globally connected, remote-first engineering group that operates in agile sprints, conducts asynchronous code reviews, and hosts regular design-thinking sessions over collaborative tools like Miro and Figma.

In this role, your workspace is wherever you do your best thinking. Whether you're inspired by the energy of a lively co-working hub or the quiet of your home office, we equip you with high-end hardware, cloud-based tools, and communication systems that make remote teamwork seamless.

Technologies, Tools, and Engineering Stack

You’ll have access to industry-standard platforms and be encouraged to experiment with cutting-edge solutions. Our current stack includes:

Programming Languages

• Python, Scala, SQL, Java

Data Engineering Tools

• Spark, Kafka, Airflow, dbt

Cloud Infrastructure

• AWS (S3, Redshift, EMR), GCP (BigQuery), Docker, Kubernetes

Machine Learning Operations

• MLflow, TensorFlow Serving, FastAPI

Monitoring and Logging

• Prometheus, Grafana, ELK Stack

We're strong proponents of open-source tools and constantly contribute back to the community. Your work will not only solve problems internally but may also inspire innovations across the industry.

Ideal Qualifications and Technical Expertise

We understand that great candidates come from a variety of backgrounds. We want to hear from you if you’re passionate about data and are driven to learn. That said, ideal candidates typically bring:

• 4+ years of experience in data engineering or data science roles
• A firm grasp of distributed systems, parallel processing, and microservice architecture
• Background in operationalizing and supporting machine learning workflows at scale
• Proficiency in cloud-native data platforms (AWS or GCP)
• Demonstrated ability to write clean, modular code with solid documentation practices
• Proven collaboration strengths and a consistent history of thriving within a remote, team-based environment

A background in applied statistics, data mining, or real-time analytics is highly desirable. Experience working with remote analytics teams or building work-from-home data engineering solutions is a significant plus.

Compensation and Remote Benefits Package

Beyond a competitive annual salary of $134,280, this role offers you long-term growth, continuous learning opportunities, and a company culture that values autonomy and collaboration. You will be given trust from day one, with the support of a team that celebrates experimentation, data-driven decisions, and ethical AI practices.

We offer flexible hours, unlimited PTO, health and wellness stipends, and access to virtual tech conferences. You’ll be recognized for what you deliver and the creativity and thought leadership you bring to your work.

Growth Paths and Career Development Opportunities

Success in this role opens multiple career pathways:

• Lead Data Architect
• Machine Learning Infrastructure Engineer
• Data Science Product Manager
• Principal Data Engineer

Your work will directly influence product recommendations, customer engagement tools, and strategic business insights. You’ll gain exposure to the full data science lifecycle, from design to deployment to feedback loops that inform future improvements.

Take the Next Step in Your Data Engineering Career

Ready to turn data into direction, models into movement, and insights into impact?

Apply today to become our next Remote Data Science Engineer and help us shape the future of data intelligence from the heart of New York City—wherever you call home.

Let’s redefine what’s possible together.