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Data Optimisation Jobs in New York (NOW HIRING)

Data Scientist (Product)

Manhattan, NY · On-site

$100 - $250/hr

You'll work on projects ranging from user-behavior insights to revenue optimization, experimentation, modeling, and building internal data tools that scale across the organization. This is a high ...

Data Architect

Teaneck, NJ

$70.25 - $90.50/hr

The Data Architect is an integral part of our Digital Information Delivery team based out of our US ... Define technical standards for medallion architecture, CDC strategy, Fabric pipelines, optimization ...

Data Architect

Teaneck, NJ · On-site

$70.25 - $90.50/hr

The Data Architect is an integral part of our Digital Information Delivery team based out of our US ... Define technical standards for medallion architecture, CDC strategy, Fabric pipelines, optimization ...

Data Architect

New York, NY · On-site

$69.75 - $89.75/hr

... optimization, scalability, data integrity, and maintainability. - Optimize SQL, execution plans, indexing, partitioning, and storage strategies. - Administer enterprise databases including backup ...

Data Engineer

Jackson, NJ · On-site

$116K - $140K/yr

The ideal candidate will be responsible for designing, building, and optimizing scalable data pipelines and high-performance data platforms. Responsibilities: * Design, develop, and maintain scalable ...

Data Architect

Manhattan, NY · On-site

$70.25 - $90.50/hr

Data Architect - III Location: New York, NY 10038 (Onsite) Duration: 12 Months Contract ... Implement cost-optimization strategies balancing compute resources, storage tiering, and cluster ...

Data Engineer

NJ · On-site

$116K - $140K/yr

The ideal candidate will be responsible for designing, building, and optimizing scalable data pipelines and high-performance data platforms. Responsibilities: * Design, develop, and maintain scalable ...

Showing results 21-40

Data Optimisation information

What are the most common challenges faced in a data optimisation role, and how can I prepare for them?

One of the main challenges in a Data Optimisation role is dealing with large, complex datasets that may have inconsistencies or missing information. You’ll often need to balance improving data quality with maintaining data integrity and system performance. Collaborating across departments, such as IT, analytics, and business operations, is typical, so strong communication skills are essential. Preparing by learning best practices in data cleaning, ETL processes, and familiarizing yourself with relevant tools will help you succeed and adapt quickly.

What are the key skills and qualifications needed to thrive as a data optimisation specialist?

To thrive as a Data Optimisation Specialist, you need strong analytical skills, proficiency in data analysis, and a background in statistics or computer science, often supported by relevant degrees or certifications. Familiarity with data management tools like SQL, Python, Excel, and optimisation platforms such as Google Analytics or Tableau is typically required. Excellent problem-solving abilities, attention to detail, and effective communication are essential soft skills for translating insights into actionable strategies. These skills ensure that data-driven decisions are accurate, impactful, and aligned with business objectives.

What are data optimisation jobs?

Data optimisation jobs involve analyzing and improving data quality, structure, and efficiency to support better decision-making and operational performance. These roles often require skills in data analysis, database management, and tools like SQL or data visualization software, with a focus on enhancing data accuracy and accessibility.

What is data optimisation?

Data optimisation refers to the process of improving the quality, accessibility, and efficiency of data within an organization. It involves cleaning, structuring, and organizing data so that it can be used more effectively for analysis, decision-making, and business operations. Data optimisation can help reduce storage costs, enhance system performance, and ensure that accurate and relevant data is available when needed. This process often includes data deduplication, compression, and the implementation of best practices for data management.

What is the difference between Data Optimisation vs Data Analysis?

AspectData OptimisationData Analysis
Primary FocusImproving data processes and system efficiencyInterpreting data to uncover insights
Skills RequiredData management, process improvement, technical skillsStatistical analysis, reporting, critical thinking
Work EnvironmentIT teams, data engineering, system optimizationBusiness units, research teams, analytics departments
CertificationsData management, database certificationsData analysis, statistical certifications

Data Optimisation focuses on enhancing data systems and processes for efficiency, while Data Analysis involves examining data to generate insights. Both roles require strong technical skills, but their objectives differ: one improves data infrastructure, the other interprets data for decision-making.

What are popular job titles related to Data Optimisation jobs in New York?

For Data Optimisation jobs in New York, the most frequently searched job titles are:

What job categories do people searching Data Optimisation jobs in New York look for?

The top searched job categories for Data Optimisation jobs in New York are:

What cities in New York are hiring for Data Optimisation jobs?

Cities in New York with the most Data Optimisation job openings:

Infographic showing various Data Optimisation job openings in New York as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 14% Part Time, 1% Temporary, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Manager, Data Science and Optimization - Retail Bank

Capital One

New York, NY • On-site

Full-time

Posted 2 days ago

New


Capital One rating

7.7

Company rating: 7.7 out of 10

Based on 147 frontline employees who took The Breakroom Quiz

91st of 171 rated banks


Job description

Manager, Data Science and Optimization - Retail Bank

Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.


As a Data Scientist at Capital One, you'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.

Team Description:

Retail Bank is a high performing modeling and analytics team that is on a mission to define the next generation of banking. The Bank team has a relentless focus on the craft of statistical modeling and innovation with a target towards continually improving decision making and delivering value to the business. Using the latest in machine learning and distributed computing technologies, you will be building the next generation of data products to enable automation and aim for the right decision at the right time for in-moment decisioning.


Role Description
In this role, you will:

  • Formulate & Solve Complex Problems: Translate ambiguous business challenges into structured mathematical problems. Design and implement optimization models (linear, mixed-integer, non-linear, and heuristic) to improve decision-making.

  • Build & Deploy Scalable Models: Develop, test, and deploy production-grade optimization algorithms and simulation models using Python and commercial/open-source solvers.

  • Collaborate Cross-Functionally: Partner closely with Product, Engineering, and Business teams to integrate optimization engines into existing software systems and workflows.

  • Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation

The Ideal Candidate is:

  • Strategic Impact & Experimental Rigor. Proven track record of driving strategic business value by optimizing customer experience funnels and risk policies, effectively evaluating external data, and institutionalizing closed-loop experimental frameworks to align predictive backtesting with live operational outcomes.

  • Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers.

  • Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.

  • Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.

Basic Qualifications:

  • Bachelor's Degree plus 6 years of experience in data analytics, or Master's Degree plus 4 years of experience in data analytics, or PhD plus 1 year of experience in data analytics

  • At least 2 years' experience in open source programming languages for large scale data analysis

  • At least 2 years' experience with machine learning

  • At least 2 years' experience with relational databases

Preferred Qualifications:

  • PhD in "STEM" field (Science, Engineering, Operations Research or Mathematics) plus 2 years of experience in data analytics

  • At least 1 year of experience working with AWS

  • At least 4 years' experience in Python, Scala, or R for large scale data analysis

  • At least 4 years' experience with machine learning

  • Experience in using numerical optimization to solve business problems

  • Experience with linear, non-linear, integer programming techniques and software packages

  • Has a track record of optimizing business outcomes and decision systems

  • Experience in formulating business problems that involves complex data, models, policy rules

  • Working experience with time-series models

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

McLean, VA: $197,300 - $225,100 for Mgr, Data Science


New York, NY: $215,200 - $245,600 for Mgr, Data Science










Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).


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