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Urgent! Director, Data Scientist - Apollo/Card Data Job Opening In McLean – Now Hiring Capital One
Overview
Director, Data Scientist - Apollo/Card DataData 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
Apollo (part of Card DMDC) is Capital One’s one stop shop for authoritative, 360 degree information on US businesses.
We are on a mission to build a market leading, business critical Business Data Product and Platform that gives our customers a competitive advantage through information.
Our customers rely on Apollo’s data and capabilities to market, sell, verify, underwrite, serve, and protect business customers, often in real-time intelligent ways.
Business data is a complex, multi-billion dollar problem that is poorly served by legacy providers.
We are tackling this critical opportunity by acquiring and processing massive amounts of data, leveraging cutting-edge ML/AI to resolve identity and predict valuable features and architecting interfaces that allow our users to seamlessly integrate Apollo into their workflows Data Science is at the heart of Apollo and this role will have an opportunity to shape the next generation of capabilities.
Role Description
In this role, you will:
Lead a team of data scientists and collaborate with machine learning engineers, data engineers, business analysts and product managers to deliver product(s) customers love.
Lead machine learning and data science technical direction and execution (operations, governance, processes and practice) working closely with product management to craft a roadmap and success criterion.
Lean on your deep technical background in graph-based machine learning, deep learning, software engineering and algorithm development to organize, grow and manage the ML/AI capabilities for the product.
Flex your interpersonal skills to translate the complexity of your work into tangible business goals
The Ideal Candidate is:
Technical Innovator.
You have a strong background in ML/AI and engineering practices with experience in Entity Resolution, Information Retrieval, Graph-based ML, LLM/Embeddings or Deep Learning.
You have hands-on experience developing effective data science solutions, while pushing the envelope with state-of-the-art techniques.
Customer-back.
Product mindset.
You are deeply curious about customer needs and bring a product mindset to drive business results, integrating ML/AI design, engineering and execution.
You identify high-leverage efforts and the necessary trade-offs to shape a roadmap that balances transformative innovation with time-to-value and pragmatism.
Empathetic People Leader.
You establish a culture of inclusiveness, cooperation and candor.
You’re passionate about talent development, provide frequent actionable feedback to team members, and promote innovation
Strategic Thinker and Communicator.
You love asking questions and pushing hard for answers.
You challenge conventional thinking and work with stakeholders to identify and improve the status quo by bringing clarity to big, undefined set the team vision, and inspire your team and peers to execute towards it.
Basic Qualifications:
Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date :
A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 9 years of experience performing data analytics
A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 7 years of experience performing data analytics
A PHD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 4 years of experience performing data analytics
At least 4 years of experience leveraging open source programming languages for large scale data analysis
At least 4 years of experience working with machine learning
At least 4 years of experience utilizing relational databases
Preferred Qualifications:
PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 5 years of experience in data analytics
At least 1 year of experience working with AWS
At least 3 year of experience managing people
At least 5 years of experience in Python, Scala, or R for large scale data analysis
At least 5 years of experience with machine learning
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.
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).Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.
Learn more at the.
Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
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Unlock Your Director Data Potential: Insight & Career Growth Guide
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Great news! Capital One is currently hiring and seeking a Director, Data Scientist Apollo/Card Data to join their team. Feel free to download the job details.
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An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at Capital One adheres to the cultural norms as outlined by Expertini.
The fundamental ethical values are:The average salary range for a Director, Data Scientist Apollo/Card Data Jobs United States varies, but the pay scale is rated "Standard" in McLean. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.
Key qualifications for Director, Data Scientist Apollo/Card Data typically include Mathematical Science Occupations and a list of qualifications and expertise as mentioned in the job specification. Be sure to check the specific job listing for detailed requirements and qualifications.
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Here are some tips to help you prepare for and ace your job interview:
Before the Interview:To prepare for your Director, Data Scientist Apollo/Card Data interview at Capital One, research the company, understand the job requirements, and practice common interview questions.
Highlight your leadership skills, achievements, and strategic thinking abilities. Be prepared to discuss your experience with HR, including your approach to meeting targets as a team player. Additionally, review the Capital One's products or services and be prepared to discuss how you can contribute to their success.
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