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Python Data Scientist Jobs in New York (NOW HIRING)

POSITION SUMMARY The Data Scientist, ITA will be a primary analytical contributor within a small ... The role requires a combination of technical depth in SQL and Python, working familiarity with ...

... Python, data science libraries, model validation methods, and modern AI/ML approaches, including generative AI where relevant, to communicate actionable insights to business and technical ...

Proficiency in Python, data analysis, visualization, and writing scalable, production-ready code using object-oriented design. * Demonstrated ability to take data science, ML, or causal inference ...

They are seeking a Data Scientist to work on data extraction, processing, and applying machine ... Java, Python, etc. • Experience in data extraction and processing, using MapReduce, Pig, Hive ...

Job Summary As a Data Scientist, you will join team that solves complex business problems for ... Proficiency in Python, SQL, and analytical tools. * Experience working with large datasets and ...

Data Scientist

Manhattan, NY · On-site

$75 - $80/hr

Data Scientist, Audience & Growth, Hybrid - New York, NY. Start date is ASAP for this contract ... Proficiency in Python or R, and SQL * Solid understanding of customer KPIs including LTV, churn ...

Senior Data Scientist

New York, NY · On-site +1

$126K - $199K/yr

Build data processing and reporting pipelines using SQL, Python, and Airflow. * Develop data ... Master's degree or foreign equivalent in Operations Research, Data Science, or related field.

Experience with SQL, Python, R, or other data-analysis tools. * Knowledge of ETL processes and data warehouse concepts. * Experience with Power Automate or other workflow-automation platforms.

About the Role As our first Data Scientist, you will leverage data to drive insights and strategies ... Proficiency in programming languages such as Python or R. * Experience with data visualization ...

Applied Physics is seeking a Data Scientist experienced with a diverse array of data types to join ... Experience developing software with C++, C, Java, Python, R, or Matlab, software applications in ...

Applied Physics is seeking a Data Scientist experienced with a diverse array of data types to join ... Experience developing software with C++, C, Java, Python, R, or Matlab, software applications in ...

Applied Physics is seeking a Data Scientist experienced with a diverse array of data types to join ... Experience developing software with C++, C, Java, Python, R, or Matlab, software applications in ...

Bedrock Robotics is hiring a Data Scientistto lead high-impact data science work across autonomy ... Proficiency in Python and SQL, with experience using modern tooling like agentic AI * Bachelor ...

Showing results 21-40

Python Data Scientist information

See New York salary details

$41K

$134.3K

$215K

How much do python data scientist jobs pay per year?

As of Sep 10, 2026, the average yearly pay for python data scientist in New York is $134,280.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,800.00 and $148,800.00 per year, depending on experience, location, and employer.

What is a Python data scientist?

A Python Data Scientist is a professional who uses Python programming language and its data analysis libraries to extract insights from large datasets. They apply statistical techniques, machine learning algorithms, and data visualization tools to solve business problems and make data-driven decisions. Python Data Scientists often work with tools like pandas, NumPy, scikit-learn, and Jupyter notebooks to manipulate data and build predictive models. Their role typically involves collecting, cleaning, analyzing, and interpreting complex data to help organizations make informed decisions.

What are some common challenges faced by Python data scientists when working with large datasets?

Python Data Scientists often encounter challenges related to processing and analyzing large datasets, such as memory limitations and slow computation times. To address these, professionals typically use libraries like Pandas, Dask, or PySpark to optimize data handling and leverage parallel computing. Collaborating closely with data engineers and IT teams can also help in setting up efficient data pipelines and scalable infrastructure. Staying updated with best practices in data preprocessing and model optimization is crucial for managing these challenges effectively.

What are the key skills and qualifications needed to thrive as a Python data scientist, and why are they important?

To thrive as a Python Data Scientist, you need strong analytical skills, a solid understanding of statistics, machine learning, and proficiency in Python programming, typically backed by a degree in computer science or a related field. Familiarity with tools and libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, and version control systems like Git is essential. Problem-solving, curiosity, and effective communication are standout soft skills for this role. These abilities are crucial for extracting actionable insights from data, building predictive models, and collaborating across multidisciplinary teams.

What is the difference between Python Data Scientist vs Data Analyst?

AspectPython Data ScientistData Analyst
Required SkillsPython, machine learning, statistical analysis, data modelingExcel, SQL, basic statistics, data visualization
CertificationsData Science certifications, Python programming coursesData analysis or business intelligence certifications
Work EnvironmentData science teams, R&D, predictive modeling projectsBusiness units, reporting, data visualization tasks
Industry UsageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Python Data Scientists focus on building predictive models and advanced analytics using Python, while Data Analysts primarily interpret data through visualization and reporting. Both roles require strong analytical skills, but Python Data Scientists typically have more programming and machine learning expertise, making them suitable for complex data projects.

How much do Python data scientists make?

Python data scientists typically earn between $80,000 and $130,000 annually, depending on experience, location, and industry. Senior roles or those with specialized skills in machine learning and big data can command higher salaries, often exceeding $150,000. Compensation may also include bonuses and stock options in some companies.

Is Python good for data science?

Python is widely used by data scientists due to its simplicity, extensive libraries like Pandas, NumPy, and scikit-learn, and strong community support. It enables efficient data analysis, modeling, and visualization, making it a preferred programming language in the data science field.

What cities in New York are hiring for Python Data Scientist jobs?

Cities in New York with the most Python Data Scientist job openings:

Infographic showing various Python Data Scientist job openings in New York as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 81% Full Time, 14% Part Time, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $134,280 per year, or $64.6 per hour.

Data Scientist

Manhattan, NY • On-site

RXinsider LTD.
Marketing • 11 - 50 employees

Other

Posted 18 days ago


Job description


AssistRx is a specialty pharmacy hub services company that manages therapy initiation and patient access programs for pharmaceutical manufacturers. The company's flagship platform, iAssist, integrates at the point of prescribing and connects patients, providers, payors, and manufacturers across complex specialty therapy programs. Welsh, Carson, Anderson & Stowe acquired AssistRx in February 2024, and the company has grown significantly, supporting a broad portfolio of programs across therapeutic areas including oncology, immunology, rare disease, and obesity.

POSITION SUMMARY

The Data Scientist, ITA will be a primary analytical contributor within a small, high-performance team. Working directly alongside the Director / VP and two peer Data Scientists, this individual will own the design and execution of analytical models, generate program insights across key KPI families, and help build the client-facing outputs — pilot QBR materials, trend narratives, analytical summaries, prototype of insight-focused dashboarding — that define the ITA value proposition.

The role requires a combination of technical depth in SQL and Python, working familiarity with statistical methods applicable to program performance analysis, and an orientation toward clear, audience-appropriate communication. Experience in pharma, pharma consulting, at a health insurer, or at a PBM is required: this work depends on understanding how specialty programs function, how manufacturers define success, and how data from hub operations connects to the broader access and reimbursement landscape.

KEY RESPONSIBILITIES Analytical Execution
  • Design and execute ad hoc and recurring analyses for ITA client engagements, covering six defined families of KPIs
  • Build and maintain analytical models within the six KPI families — from patient outcomes through data quality — ensuring consistent definitions, reproducible methodology, and appropriate statistical rigor
  • Develop cohort analyses, funnel decompositions, survival curves, regression models, and distribution-based performance metrics that surface actionable insights within program data
  • Identify trends, anomalies, and comparative performance differentials across programs, payors, geographies, and time periods; frame findings as hypotheses with supporting evidence
Client-Facing Output Development
  • Contribute to quarterly business review (QBR) preparation, including data pulls, visualization development, and narrative drafting under the direction of the Director / VP
  • Produce clean, client-ready analytical exhibits — charts, tables, and written summaries — formatted for manufacturer audiences including market access leadership and patient services teams
  • Participate in select client meetings as a technical resource; communicate methodology and findings clearly to non-technical stakeholders
Productization & Documentation
  • Define analytical specifications and prototype outputs for validated insights; partner with the dedicated BI and report development team to translate ITA analytical work into productized ThoughtSpot and Power BI dashboards — ITA owns the logic, acceptance criteria, and narrative framing; the report development team handles production build
  • Maintain clear documentation of analytical methodologies, data transformations, and code to support reproducibility and team knowledge management
  • Surface upstream data quality issues that affect insight reliability; partner with data governance teams on remediation
Continuous Improvement
  • Contribute to the evolution of the ITA analytical framework as new client engagements reveal novel questions and additional KPI families emerge
  • Stay current on emerging methods in healthcare analytics, specialty pharmacy data, and applied machine learning relevant to program performance and patient journey analysis
REQUIRED QUALIFICATIONS
  • Approximately 5 years of experience in healthcare analytics, with direct experience in one or more of the following: pharmaceutical manufacturer (commercial, market access, or patient services analytics), pharma consulting, health insurer, or pharmacy benefit manager (PBM)
  • Strong proficiency in SQL; experience querying and manipulating data in cloud data warehouse environments (Snowflake preferred)
  • Python or R required; Python preferred (pandas, numpy, scipy, and scikit-learn)
  • Working knowledge of statistical methods applicable to program performance analysis: cohort analysis, survival analysis, funnel decomposition, regression modeling, distribution-based metrics, and experimental design and A/B testing frameworks
  • Experience producing structured, audience-ready analytical outputs — not just raw analyses; strong attention to how findings are communicated, not just computed
  • Clear, organized written and verbal communication skills; ability to explain quantitative findings in plain language
  • Bachelor's degree in a quantitative field (statistics, mathematics, data science, computer science, economics, or related); advanced degree a plus
PREFERRED QUALIFICATIONS
  • Familiarity with pharmaceutical hub program workflows, including case management, prior authorization, benefits verification, payor adjudication, and patient financial assistance programs
  • Experience working with specialty pharmacy data structures and source systems (CRM, pharmacy dispensing platforms, benefits verification systems)
  • Background in patient access or market access analytics at a pharmaceutical manufacturer, including program KPI development and payor-level performance analysis
  • Analytical experience at a health insurer or PBM, particularly in formulary analytics, specialty drug utilization, or patient access reporting
  • Experience with ThoughtSpot or Power BI preferred
  • Exposure to or curiosity about generative AI and its applications in analytics workflows (natural language querying, entity resolution, or automated insight generation)
  • Experience contributing to a client-facing analytics product or repeatable analytical framework
  • Familiarity with dbt or similar data transformation frameworks
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