Data Scientist Jobs in New York | Entry to Senior Level AI & ML Careers

August 1, 2026 - By Cybotrix Technologies

Location: New York, NY, USA
Experience: Entry Level to Senior Professionals (0–12+ Years)
Employment Type: Full-Time | Hybrid | Remote | Contract Opportunities
Salary Range: USD $90,000 – $260,000+ Per Year (Based on experience, employer, and technical expertise)

Data Scientist Jobs in New York – Launch or Advance Your Data Science Career

New York is one of the world’s leading technology and financial hubs, creating exceptional demand for skilled Data Scientists across industries including banking, healthcare, fintech, insurance, retail, media, artificial intelligence, e-commerce, cybersecurity, pharmaceuticals, consulting, telecommunications, and cloud technology.

Organizations are investing heavily in Artificial Intelligence (AI), Machine Learning (ML), Predictive Analytics, Big Data, Natural Language Processing (NLP), Computer Vision, Business Intelligence, and Generative AI to gain competitive advantages. As a result, professionals with strong analytical and programming skills continue to command premium salaries.

Whether you are a recent graduate, junior analyst, experienced data scientist, AI specialist, or principal data science leader, New York offers outstanding career opportunities with startups, Fortune 500 companies, investment banks, healthcare organizations, and global technology firms.

Job Overview

We are seeking passionate, analytical, and technically skilled Data Scientists capable of transforming complex business data into actionable insights using modern statistical techniques, machine learning algorithms, and advanced analytics.

The ideal candidate should possess expertise in data mining, predictive modeling, AI solutions, cloud analytics, and visualization technologies while collaborating with engineering, product, and business stakeholders.

Key Responsibilities

Analyze structured and unstructured datasets from multiple business sources.
Develop predictive models using machine learning algorithms.
Build scalable data science pipelines for enterprise applications.
Perform exploratory data analysis (EDA) to identify hidden patterns.
Design recommendation systems and forecasting models.
Develop customer segmentation and behavioral analytics models.
Build fraud detection, anomaly detection, and risk analytics solutions.
Implement Natural Language Processing (NLP) models.
Develop AI-driven business intelligence solutions.
Deploy ML models using cloud platforms.
Optimize model performance using feature engineering techniques.
Work closely with Data Engineers and ML Engineers.
Build interactive dashboards and executive reports.
Perform A/B testing and statistical hypothesis validation.
Design data-driven strategies supporting business decisions.
Develop Generative AI and Large Language Model (LLM) applications where applicable.
Ensure data governance, compliance, and security best practices.
Document methodologies and technical solutions.
Mentor junior team members and review model quality.
Continuously research emerging AI technologies and industry trends.

Required Technical Skills

Category	Required Skills
Programming	Python, R, SQL
Machine Learning	Supervised Learning, Unsupervised Learning, Reinforcement Learning
Deep Learning	TensorFlow, PyTorch, Keras
Data Processing	Pandas, NumPy, SciPy
Big Data	Apache Spark, Hadoop, Hive
Visualization	Power BI, Tableau, Matplotlib, Seaborn, Plotly
Databases	PostgreSQL, MySQL, SQL Server, MongoDB
Cloud	AWS, Microsoft Azure, Google Cloud Platform
MLOps	MLflow, Kubeflow, Docker, Kubernetes
Version Control	Git, GitHub, GitLab
Deployment	REST APIs, FastAPI, Flask
AI Technologies	LLMs, Generative AI, OpenAI APIs, LangChain, Vector Databases
Data Engineering	ETL, ELT, Data Warehousing
DevOps	CI/CD Pipelines
Statistics	Regression, Bayesian Statistics, Time Series Analysis
Business Analytics	KPI Development, Forecasting, Optimization

Preferred Qualifications

Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, Artificial Intelligence, Engineering, or a related discipline.
PhD candidates are encouraged to apply for advanced research roles.
Strong understanding of machine learning lifecycle.
Hands-on experience with production ML systems.
Knowledge of cloud-native analytics platforms.
Excellent problem-solving and analytical thinking.
Strong communication and presentation abilities.
Experience working in Agile development environments.

Experience Levels

Entry Level (0–2 Years)

Ideal for fresh graduates with internship or project experience.

Responsibilities include:

Data cleaning
SQL querying
Dashboard creation
Basic predictive modeling
Data visualization
Statistical reporting

Mid-Level (3–6 Years)

Professionals should be capable of:

Developing production-grade ML models
Feature engineering
Cloud deployment
Building recommendation systems
Customer analytics
Business forecasting

Senior Level (7–12+ Years)

Senior professionals will lead:

Enterprise AI initiatives
Data science strategy
Team leadership
Model governance
AI architecture
Cross-functional stakeholder management
Large-scale analytics transformation projects

Desired Soft Skills

Analytical thinking
Business problem solving
Leadership
Innovation mindset
Stakeholder communication
Critical thinking
Decision making
Collaboration
Presentation skills
Adaptability
Time management
Mentoring capabilities

Career Growth Path

Junior Data Scientist
Data Scientist
Senior Data Scientist
Lead Data Scientist
Principal Data Scientist
Machine Learning Engineer
AI Engineer
Applied Scientist
Research Scientist
Data Science Manager
Director of Data Science
Head of AI
Chief Data Officer (CDO)

Why Build Your Career in New York?

New York continues to be among the highest-paying markets for data professionals due to its concentration of global enterprises, investment firms, healthcare innovators, and AI-driven technology companies. Professionals gain exposure to enterprise-scale datasets, cutting-edge AI research, cloud-native architectures, and cross-functional digital transformation initiatives while working on impactful business challenges.

With increasing adoption of Artificial Intelligence, Machine Learning, Big Data Analytics, Predictive Modeling, Business Intelligence, Generative AI, and Cloud Data Platforms, employers are actively seeking professionals who can convert data into strategic business value.

Benefits

Competitive Salary Packages
Annual Performance Bonus
Stock Options (Company Dependent)
Medical Insurance
Dental & Vision Coverage
401(k) Retirement Benefits
Paid Vacation
Flexible Work Arrangements
Hybrid & Remote Opportunities
Learning and Certification Support
AI & Cloud Training Programs
Leadership Development
International Project Exposure
Employee Wellness Programs
Career Advancement Opportunities

Top Technologies Employers Look For

Python • SQL • R • TensorFlow • PyTorch • Scikit-learn • Pandas • NumPy • Spark • Hadoop • Kafka • Databricks • Snowflake • PostgreSQL • Tableau • Power BI • AWS • Azure • Google Cloud Platform • Docker • Kubernetes • MLflow • Airflow • FastAPI • Flask • LangChain • OpenAI API • Vector Databases • Pinecone • ChromaDB • Redis • Git • GitHub

Why Apply?

If you are passionate about solving real-world business challenges using Artificial Intelligence, Machine Learning, Predictive Analytics, and Data Science, New York provides exceptional opportunities to accelerate your career. Organizations across finance, healthcare, technology, retail, and consulting continue to invest heavily in AI-driven innovation, making this an ideal time to pursue entry-level, mid-level, or senior Data Scientist roles.

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