Data Science Jobs in New York

Last Updated : 03 May, 2024

Data science is a burgeoning field that intertwines technology, mathematics, and business acumen to derive actionable insights from vast volumes of data. In the bustling metropolis of New York, the demand for skilled data scientists continues to surge across various industries. This guide serves as a roadmap for aspiring data scientists, offering insights into companies actively seeking talent, prominent job portals, salary trends, and additional details to navigate the vibrant job market of New York City.

Roles and Responsibilities of Data Scientists:

Data scientists play a pivotal role in extracting actionable insights from vast and complex datasets. Their responsibilities encompass a wide array of tasks aimed at leveraging data to inform strategic decisions and drive business growth.

Here are the key roles and responsibilities of data scientists:

Data Collection and Cleaning:

Gather data from various sources including databases, APIs, and external datasets.
Clean and preprocess data to remove inconsistencies, errors, and missing values.
Perform data wrangling and transformation to prepare datasets for analysis.

Exploratory Data Analysis (EDA):

Conduct exploratory data analysis to understand the structure, patterns, and relationships within the data.
Visualize data using charts, graphs, and other statistical techniques to uncover insights.
Identify outliers, trends, and correlations that may influence decision-making.

Statistical Analysis and Modeling:

Apply statistical techniques and machine learning algorithms to analyze data and extract meaningful patterns.
Develop predictive models to forecast future trends, outcomes, or behavior.
Evaluate model performance and iterate on algorithms to improve accuracy and reliability.

Feature Engineering:

Engineer features from raw data to enhance model performance and predictive power.
Select relevant variables and create new features based on domain knowledge and data understanding.
Utilize techniques such as dimensionality reduction and feature scaling to optimize model training.

Model Deployment and Monitoring:

Deploy machine learning models into production environments for real-time inference.
Implement monitoring systems to track model performance, data drift, and model degradation.
Collaborate with software engineers to integrate models into scalable and reliable applications.

Business Insights and Recommendations:

Translate data findings into actionable insights and strategic recommendations for stakeholders.
Communicate complex technical concepts and analytical results to non-technical audiences effectively.
Collaborate with cross-functional teams to align data-driven solutions with business objectives.

Experimentation and A/B Testing:

Design and conduct experiments to test hypotheses and evaluate the impact of interventions.
Analyze experimental results using statistical methods to make data-driven decisions.
Optimize strategies based on insights gained from A/B testing and continuous experimentation.

Data Governance and Compliance:

Ensure data quality, integrity, and security throughout the data lifecycle.
Adhere to regulatory requirements and industry standards related to data privacy and compliance.
Implement data governance policies and procedures to maintain data consistency and confidentiality.

Continuous Learning and Skill Development:

Stay abreast of advancements in data science, machine learning, and related fields.
Engage in continuous learning through courses, workshops, and conferences to enhance skills and knowledge.
Experiment with new tools, technologies, and methodologies to improve productivity and effectiveness.

Cross-Functional Collaboration:

Work collaboratively with interdisciplinary teams including data engineers, business analysts, and domain experts.
Engage in knowledge sharing and mentorship to foster a culture of data-driven decision-making across the organization.
Act as a subject matter expert and provide guidance on best practices in data science and analytics.

Companies Hiring Data Scientists in New York

New York boasts a vibrant ecosystem of companies seeking skilled data scientists. Here are some prominent names actively recruiting in the field:

Google

Requirements:

Bachelor’s degree in Computer Science, Statistics, Mathematics, or related field.
Proficiency in programming languages like Python, R, or Java.
Strong analytical and problem-solving skills.

Apply Here: Careers

Facebook

Requirements:

Master’s or Ph.D. in Computer Science, Statistics, Economics, or equivalent.
Experience with data analysis tools such as SQL, R, or Python.
Ability to work collaboratively in a fast-paced environment.

Apply Here: Careers

Apple Inc.

Requirements:

Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field.
Proficiency in machine learning algorithms and data visualization techniques.
Excellent communication and teamwork skills.

Apply Here: Careers

Amazon

Requirements:

Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or related field.
Hands-on experience with big data technologies like Hadoop, Spark, or AWS.
Strong problem-solving and critical-thinking abilities.

Apply Here: Careers

Netflix

Requirements:

Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related discipline.
Expertise in data mining, statistical analysis, and machine learning techniques.
Ability to thrive in a dynamic and fast-paced environment.

Apply Here: Careers

Uber

Requirements:

Bachelor’s degree in Computer Science, Engineering, Mathematics, or equivalent.
Proficiency in programming languages such as Python, Java, or Scala.
Strong analytical skills and attention to detail.

Apply Here: Careers

Airbnb

Requirements:

Master’s degree in Computer Science, Statistics, Economics, or related field.
Experience with data manipulation and analysis using tools like Pandas, NumPy, or SQL.
Excellent problem-solving and communication skills.

Apply Here: Careers

Twitter

Requirements:

Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field.
Familiarity with machine learning algorithms and natural language processing techniques.
Ability to work effectively in a collaborative team environment.

Apply Here: Careers

Requirements:

Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or equivalent.
Strong proficiency in data analysis and visualization tools such as Tableau, Power BI, or Matplotlib.
Effective communication and presentation skills.

Apply Here: Careers

Adobe

Requirements:

Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.
Experience with statistical analysis tools and techniques.
Ability to manage and analyze large datasets efficiently.

Apply Here: Careers

NVIDIA

Requirements:

Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or Mathematics.
Proficiency in deep learning frameworks such as TensorFlow, PyTorch, or Caffe.
Strong problem-solving and debugging skills.

Apply Here: Careers

Intel Corporation

Requirements:

Master’s or Ph.D. in Computer Science, Statistics, Mathematics, or related field.
Experience in data preprocessing, feature engineering, and model evaluation.
Excellent programming skills in languages like Python, C++, or Java.

Apply Here: Careers

Salesforce

Requirements:

Bachelor’s or Master’s degree in Computer Science, Statistics, or a related field.
Hands-on experience with data analysis and visualization tools.
Strong interpersonal and communication skills.

Apply Here: Careers

PayPal

Requirements:

Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field.
Proficiency in data analysis and machine learning techniques.
Ability to work independently and collaboratively.

Apply Here: Careers

Oracle

Requirements:

Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
Experience with database management systems and SQL programming.
Strong problem-solving and analytical skills.

Apply Here: Careers

Job Portals

For those seeking data science roles in New York, the following job portals can be valuable resources:

Salary of Data Scientists in New York

Salaries for data scientists in New York can vary based on factors such as experience, education, and location. Here’s a general overview:

Entry-level: $80,000 – $120,000 per year

Mid-level: $120,000 – $160,000 per year

Senior-level: $160,000 – $250,000+ per year

Experience-Wise Salary Trend

Less than 2 years: $80,000 – $120,000 per year

2-5 years: $120,000 – $160,000 per year

5-10 years: $160,000 – $200,000 per year

10+ years: $200,000+ per year