Senior Associate, Data Science
Capital One · Bengaluru · onsite · Posted 2d ago
Undisclosed2–7 yrsfulltimeSourced from
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About this role
Job Summary
Team Description
Role Description
The ideal candidate is:
Basic Qualifications:
Preferred Qualifications:
Senior Associate, Data Science at Capital One India, Bangalore. As a Data Scientist, you will be part of a team that is leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies to unlock the big opportunities that help drive efficiency and improve customer experience. You will do it in a collaborative environment that values your insight, encourages you to take on new responsibility, promotes continuous learning, and rewards innovation.
Team Description
The Model Risk Management team acts as a critical line of defense, identifying and mitigating risks associated with the banks most sophisticated decision-making systems. We combine statistics, software engineering, and business expertise to drive the best outcomes for the Enterprise, ensuring that every model from deposits pricing to fraud detection is robust and reliable. We invest heavily in new skills and building better tools to govern emerging technologies like Generative AI. Our team thrives on a rigorous challenge culture to develop increasingly powerful validation techniques that ensure model integrity and regulatory compliance.
Role Description
General responsibilities include but are not limited to:
- Partner cross-functionally with teams throughout the enterprise including Product and Tech to deliver solutions. You will enhance your technical and analytical skills, while also working with leaders to influence business strategies.
- Collaborate with Quants, Data Scientists, Data analysts, Business analysts and risk managers to drive innovation, and shape strategic initiatives.
- Utilize data to drive real-world impact and thrive in a collaborative, forward-thinking environment.
- Assess, challenge, and at times defend state-of-the-art decision-making systems to internal and regulatory partners.
- Build upon your existing machine learning and statistical toolset - both by learning new technologies and by building custom software tools for data exploration, model performance evaluation, and more.
- Use Open Source/Digital technologies to mine complex, voluminous, and different varieties of data sources and platforms.
- Build well-managed data products, data solutions, tools, and capabilities to enable self-service frameworks for data consumers.
- Demonstrate ability to explore and quickly grasp new technologies to progress varied initiatives.
- Drive analysis that provides meaningful insights on business strategies.
- Communicate technical subject matter clearly and concisely to individuals from various backgrounds both verbally and through written communication; prepare presentations of complex technical concepts and research results to non-specialist audiences and senior management.
- Flex your interpersonal skills to defend the model with validators, auditors and regulators.
The ideal candidate is:
- Inquisitive: You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You are not afraid to share a new idea.
- 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.
- Quantitative and ML/Statistically-minded: You ve built models, validated them, and worked with them.
- Thrive in a dynamic and fast-paced environment: You are comfortable with ambiguity and enjoy cutting through distractions to discern priorities and create structure where none exists.
- You understand the big picture but are also able to execute with close attention to detail.
- 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.
Basic Qualifications:
- Bachelor's degree in statistics, math, engineering, economics, econometrics, finance or operations research with a quantitative focus.
- At least 2 years of experience in data analytics.
- At least 1 year's experience in Python or R.
Preferred Qualifications:
- 2+ years of experience in model development or validation.
- 2+ years of experience in R or Python for large scale data analysis.
- 2+ years of experience with relational databases and SQL.
- Strong analytical skills with high attention to detail and accuracy.
- Excellent written and verbal communication skills.
- Experience in the financial services industry.
- Proficiency in key econometric and statistical techniques, model design, development and deployment experience
- Experience in evaluating and working with emerging technologies and algorithms.
At this time, Capital One will not sponsor a new applicant for employment authorization for this position.
Sourced from naukri
Skills
Customer Experienceanalytical thinkingCloud Computingdata scientistAnalyticsData AnalyticsdeploymentDevelopment And Deploymentcloudcredit cardCommunication SkillsAlgorithmsdata analysiscomplianceData ScienceArtificial Intelligence
About CapitalOne
Capital One
FinTech
175
employees
1994
32 years old
McLean
United States
About
Capital One helps customers find the right credit cards, checking or savings accounts, auto loans, and other banking services for them & their businesses.
Industries
FinTechBanking / Insurance / AccountingFinancial Services
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