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Temporary Data Science R Jobs in New York (NOW HIRING)

Publicis Groupe Holdings B.V

Data Scientist

Manhattan, NY · On-site

$72K - $109K/yr

... Data Science practice. Qualifications We're looking for relevant academic, research or work ... Hands-on experience with Python or R. Familiarity with SQL, Linux, and/or distributed computing ...

Fanatics

Data Scientist

Manhattan, NY · On-site

... science, analytics, or a related quantitative role. • Working knowledge of SQL and experience querying large datasets. • Proficiency in Python or R for data analysis. • Foundational ...

Florvets Structures

Data Scientist

New York, NY

... science and bring new ideas and techniques to the team - Ensure data integrity and security by ... Python, R, and SQL - Experience with data visualization tools such as Tableau or Power BI ...

Oscar Health

Data Scientist II

New York, NY · Hybrid

$131K - $172K/yr

... science, applied analytics, or a related quantitative field (industry, academia, or both) * 2+ years of experience using SQL and Python and/or R to query, analyze, and manipulate data * 2+ years of ...

Forhyre

Data Scientist

New York, NY

Knowledge of R, SQL and Python; familiarity with Scala, Java or C++ is an asset * Experience using ... BSc/BA in Computer Science, Engineering or relevant field; graduate degree in Data Science or other ...

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What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or data features. Data scientists often focus on the most impactful variables or tasks to optimize model performance and efficiency.

What jobs can you get knowing R?

Knowing R can qualify you for roles such as data analyst, data scientist, statistical programmer, or research analyst. These jobs involve data manipulation, statistical analysis, and visualization, often requiring familiarity with R packages like ggplot2 or dplyr and sometimes additional skills in SQL or Python.

Will AI replace data scientists in 2050?

As a temporary data science R, AI is expected to augment rather than replace data scientists by automating routine tasks and enhancing data analysis capabilities. Data scientists will continue to be essential for interpreting complex data, developing models, and applying domain expertise, especially as tools like machine learning frameworks evolve. Adaptability and skills in programming, statistics, and AI tools will remain valuable in the future job market.

Is 40 too late for data science?

Age is not a barrier to entering data science, and many professionals start or transition into the field later in life. Success depends on acquiring relevant skills such as programming, statistics, and tools like Python or R, along with practical experience. Continuous learning and adapting to industry trends are key regardless of age.
What are the most commonly searched types of Data Science R jobs in New York? The most popular types of Data Science R jobs in New York are:
What cities in New York are hiring for Temporary Data Science R jobs? Cities in New York with the most Temporary Data Science R job openings:
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Executive Director - AI Data Science

Career Renew

New York, NY • On-site

$299K - $409K/yr

Full-time

Posted 4 days ago

Job description

Career Renew is recruiting for one of its clients an Executive Director - AI Data Science - this is an onsite role in Santa Monica or New York.
We are a strategic partner to organizations re-engineering their business around unified intelligence.Helping enterprises move beyond AI adoption to intelligence-led transformation, we deliver connected solutions that maximize output, decision-making, and deliver competitive advantage.

About the Role

As Executive Director on the AI Science team, you will lead the design and execution of high-impact AI and data science initiatives across our fixed income and investment banking businesses. Reporting to the Managing Director of AI & Data, you will act as the senior technical leader for the function. You will drive enterprise-critical projects, set technical direction, and mentor a small team of data scientists working on pricing, risk, and capital markets problems.

You will partner closely with traders, bankers, risk leaders, and senior executives to align data science solutions with the firm's commercial priorities, ensuring advanced AI and quantitative methods are adopted responsibly and at scale. This role demands deep technical expertise in both machine learning and the mechanics of fixed income markets, paired with the ability to influence decision-makers and deliver measurable outcomes on the desk and across the enterprise.


Key Responsibilities

  • Lead flagship AI/ML projects that drive measurable value across fixed income trading, credit, rates, and investment banking workflows, from pricing and execution to risk and origination.

  • Direct the development of models for valuing illiquid instruments, forecasting price and spread movements, modeling prepayment and default risk, and analyzing the yield curve and interest rate dynamics.

  • Act as senior technical authority on advanced AI methods (generative AI, causal inference, LLM-based analytics, RAG, simulation) and on their application to quantitative finance.

  • Translate complex desk-level and banking challenges into enterprise-grade data science solutions with tangible P&L and risk-adjusted ROI.

  • Mentor and guide a small team of data scientists, building technical excellence, modeling rigor, and responsible AI adoption.

  • Partner with trading desks, banking coverage teams, risk, MDs, and executive committees to ensure AI initiatives align with firm-wide priorities.

  • Represent TWG Global in external technical forums and partnerships with universities, regulators, and technology leaders.

  • Define standards for experimentation, reproducibility, and model governance, consistent with the controls expected in a regulated capital markets environment.

  • Stay ahead of emerging trends in AI/ML and quantitative finance, advising on adoption and firm-wide capability building.

Requirements:
10+ years of experience in data science/ML applied to fixed income or capital markets (Mandatory)
Data science or machine learning background serving enterprise customers and delivering enterprise level impact (Mandatory)
Led projects in fixed income, capital markets, or quantitative finance (Mandatory)
Experience mentoring or managing a small data science team (Mandatory)
Master's or higher in Data Science, Statistics, Computer Science, Financial Engineering, Quantitative Finance, or a related discipline.(Mandatory)
Deep expertise in ML: advanced machine learning, causal inference, deep learning, statistical modeling, and time series analysis (Mandatory)
Hands-on technical depth in Python (or R), cloud-based platforms, and modern ML frameworks (Mandatory)
Working knowledge of fixed income fundamentals: duration, convexity, yield curves, credit spreads, rate models, and the pricing of debt instruments and derivatives (Mandatory)
Experience with Palantir platforms (e.g., Foundry/AIP/Ontology) (Nice-to-have)
Familiarity with vector databases, knowledge graphs, and LLM application frameworks for advanced analytics (Nice-to-have)
Cloud or AI/ML certifications (e.g., AWS ML Specialty, Google Cloud ML Engineer, Azure AI Engineer) (Nice-to-have)
Proven ability to influence senior stakeholders (MDs, traders, executives) - must be credible to a very senior, technical audience (Mandatory)