data science manager

Nissan Motor Corporation

<div>
 
 
 Responsibilities:
 
 
 <ul>
 <li>
 Lead and manage data science teams, overseeing the development and deployment of machine learning models and advanced analytics solutions.
 </li>
 <li>
 Define and execute data strategies aligned with business objectives, ensuring actionable insights drive decision-making.
 </li>
 <li>
 Collaborate with cross-functional teams, including engineering, product, and business stakeholders, to identify and solve complex data-related challenges.
 </li>
 <li>
 Ensure data integrity, governance, and security while optimizing data pipelines and infrastructure for scalability.
 </li>
 <li>
 Mentor and develop data scientists, providing technical guidance, performance feedback, and career development support.
 </li>
 <li>
 Stay updated on emerging trends, technologies, and best practices in data science and artificial intelligence (AI).
 </li>
 <li>
 Communicate findings effectively to both technical and non-technical stakeholders, translating insights into business impact.
 </li>
 </ul>
 
 
 Key Competencies:
 
 
 <ul>
 <li>
 Strong problem-solving and analytical thinking skills to interpret complex data and drive insights.
 </li>
 <li>
 Leadership and people management abilities to guide and grow a high-performing data science team.
 </li>
 <li>
 Business acumen to align data science initiatives with organizational goals and drive measurable value.
 </li>
 <li>
 Effective communication skills for conveying technical concepts to diverse audiences.
 </li>
 <li>
 Decision-making capabilities based on data-driven approaches.
 </li>
 </ul>
 
 
 Technical Skills:
 
 
 <ul>
 <li>
 Proficiency in programming languages such as Python, R, or SQL.
 </li>
 <li>
 Expertise in machine learning frameworks (TensorFlow, PyTorch, Scikit-Learn).
 </li>
 <li>
 Experience with big data technologies (Spark) and cloud platforms (
 
 AWS/
 
 Azure/ GCP).
 </li>
 <li>
 Strong understanding of statistical modeling, predictive analytics, and deep learning.
 </li>
 <li>
 Experience with data visualization tools (Quicksight, Power BI, Matplotlib, Seaborn, Streamlit/Dash).
 </li>
 <li>
 GenAI: Experience with GenAI APIs, LLMs, Vectorization, Agentic AI and prompt engineering for domain-specific solutions
 </li>
 <li>
 MLOps: Ability to build reusable model pipelines and manage deployments using MLflow and Docker
 </li>
 </ul>
 
 
 Behavioural Competencies:
 
 
 <ul>
 <li>
 Adaptability: Ability to pivot strategies based on evolving business needs and technological advancements.
 </li>
 <li>
 Learning Agility: Continuous learning mindset to keep up with emerging data science trends and methodologies.
 </li>
 <li>
 Teamwork: Collaborative approach to working with cross-functional teams, fostering knowledge sharing and innovation.
 </li>
 </ul>
 
 
 Certifications (Optional):
 
 
 <ul>
 <li>
 Certified Data Scientist (CDS) &ndash; DASCA
 </li>
 <li>
 AWS Certified Machine Learning &ndash; Specialty
 </li>
 <li>
 Microsoft Certified: Azure AI Engineer Associate
 </li>
 <li>
 Coursera/edX Data Science Specializations (e.g., IBM, Stanford, Harvard)
 </li>
 <li>
 Data Engineering Certifications
 </li>
 </ul>
 
 
 
 
 
 
 
 
 
 
 Location : Trivandrum Kerala Ind
 
 
 
 
 
 ia
</div>

Data Science Manager

Moniepoint

<div>Who we are

Moniepoint is a global fintech building modern financial services for millions of people and businesses across high-growth markets. We provide payments, banking, credit, and financial management tools, reliable products that people and businesses use every day to run their lives, grow their companies, and move money safely.

Our mission is simple: to enable financial happiness for every African, everywhere. And this is day one. We've grown rapidly in Nigeria and the UK, and we're now expanding our product, engineering, and analytics teams. Our work ranges from building financial infrastructure to designing intuitive customer experiences, solving real, meaningful problems at scale.

Job Purpose

The Data Science Manager (Fraud) leads our fraud decisioning efforts to ensure Moniepoint remains the most trusted financial partner for our users.

In this role, you'll own the vision and execution of our fraud detection and prevention models. You aren't just building algorithms; you're making real-time decisions that protect millions of customers. You'll lead a team of specialists to create innovative solutions for customer screening, transaction monitoring, and authentication, ensuring our growth is backed by world-class security.

Key Responsibilities
<ul>
<li>Set the Strategy: Build and scale the roadmap for fraud decisioning, ensuring our models stay ahead of emerging typologies.</li>
<li>Lead the Team: Mentor and develop a team of data scientists, fostering a culture of mastery and continuous learning.</li>
<li>Architect Solutions: Partner with Product and Engineering to design and deploy real-time decision logic and data architectures.</li>
<li>Model Mastery: Develop fraud scoring methodologies and build features from high-volume transactional, device, and behavioural data.</li>
<li>Optimise Outcomes: Design and run experiments to improve precision and recall, balancing security with a seamless user experience.</li>
<li>Governance &amp; Integrity: Ensure data quality and the responsible use of models within our regulated environments.</li>
<li>Continuous Monitoring: Keep a pulse on model performance and drift, ensuring our defences evolve as fast as the threats do.</li>
</ul>
Qualifications
<ul>
<li>6+ years of experience in Data Science, Decision Science, or Fraud Risk, ideally within financial services.</li>
<li>A degree or equivalent experience in a quantitative field (Statistics, Mathematics, Engineering, or similar).</li>
<li>Deep knowledge of fraud typologies, financial crime, and the regulatory landscape.</li>
<li>Proficiency in SQL and at least one programming language (Python is our primary tool).</li>
<li>Demonstrated success in building and deploying machine learning models at scale.</li>
<li>Experience leading or mentoring technical teams in a fast-paced environment.</li>
<li>Preferred Qualifications</li>
<li>Experience with A/B testing and experimentation in real-time environments.</li>
<li>Familiarity with churn management and user retention modelling.</li>
<li>Advanced degree (MSc or PhD) in a related quantitative field.</li>
</ul>
About you
<ul>
<li>You're a systems thinker: You see the patterns in data and know how to turn them into scalable defences.</li>
<li>You have grit: You're comfortable navigating the ambiguity of a high-growth scale-up and driving momentum through continuous improvement.</li>
<li>You value mastery: You're deeply technical but can translate complex analyses into clear, actionable stories for any stakeholder.</li>
<li>You're human-centric: You understand that behind every data point is a person's financial happiness, and you're driven to protect it.</li>
</ul>
What Success Looks Like
<ul>
<li>Reliable Defences: Our fraud detection systems are highly accurate, maintaining a world-class balance between precision and recall.</li>
<li>Team Growth: Your team feels supported, clear on their progression, and empowered to do their best work.</li>
<li>Seamless Integration: Fraud decision logic is embedded into our products without creating unnecessary friction for our honest users.</li>
<li>Data Integrity: Our models are well-documented, compliant, and consistently monitored for performance and bias.</li>
</ul>
What we can offer you
<ul>
<li>Culture: We put our people first. We've built a company where all voices are heard and where we value each other as humans.</li>
<li>Learning: We're a knowledge-sharing environment with regular technical talks and a focus on training.</li>
<li>Compensation: You'll receive an attractive salary, pension, health insurance, annual bonus, and other benefits.</li>
</ul>
What to expect in the hiring process
<ul>
<li>Recruiter Call: A preliminary chat with one of our recruiters.</li>
<li>Take-home Task: A SQL and anomaly detection modelling case study.</li>
<li>Task Review: A session with our Engineering Manager and Head of Data Science.</li>
<li>Technical Interview: A deep dive with the Head of Data Science.</li>
<li>Behavioural Interview: A conversation with our VP of Engineering and a Business Leader.</li></ul></div>

Data Science Manager (Fraud)

The Home Depot

<div>Position Purpose:
We are transforming how merchandising decisions are made through AI-powered solutions and automation. The Data Science Manager &ndash; Micro Space Intelligence plays a critical role in the technical design and delivery of AI-enabled planogram automation capabilities. This role partners closely with Strategy and Process teams to ingest business requirements and translate them into a scalable technical roadmap, overseeing the development of business rules, AI/ML algorithms, and optimization techniques that accurately reflect merchandising intent. As the technical owner of the solution, this leader designs the end-to-end technical strategy to integrate tools and platforms together into a cohesive, scalable process, ensuring the underlying math, automation logic, and learning systems are sound, efficient, and adaptable.
As a people and technical leader, the Data Science Manager leads and mentors a team of data scientists and solution engineers, setting coding standards, QA processes, and deployment best practices to ensure solutions are robust, maintainable, and production-ready. Acting as a trusted technical advisor to Strategy and business partners, this role evaluates proposed initiatives for technical feasibility, identifies advanced analytical and AI opportunities, and translates high-level business goals into impactful automated systems. The role also collaborates closely with fellow Data Science Managers to align approaches, manage talent effectively, and deliver clear, executive-level communication that drives alignment across all levels of the organization. 
Key Responsibilities:<ul><li>
40% People Management &amp; Team Leadership - Provide leadership, mentorship and coaching to Data Scientists (individual contributors) and evaluate performance, execution, and contribution; Attract, retain and develop top talent to build an effective and high performing team; Support team in development of business knowledge and technical skills with clear plans and regular assessment of progress; Ensure appropriate processes and job-specific requirements are properly documented; Develop onboarding and training plan for both technical and soft skills that will ensure high level of capabilities within the team; Manage resources effectively to align with strategic initiatives and business needs; Foster collaboration with team members to develop a supportive and engaged team; Support team in the design and development of algorithms and models to use against large datasets to create business insights; Drive team's results and celebrate accomplishments</li><li>
25% Project Management - Prioritize and assign projects by striking a balance between a variety of factors, like funding, return on investment, innovative or challenging work, among others; Manage programs for the team to ensure consistency of execution, balance of resources and quality solutions; Collaborate with program managers and business partners to align on objectives and expectations and ensure project teams deliver against them; Serve as escalation point for any issues or difficulties with specific projects; Provide executive updates to leaders at all levels of the organization on program effectiveness, team accomplishments, summary of findings and recommended solution, and explain internal and external impacts</li><li>
15% Strategy &amp; Business Development - Leverage extensive business knowledge and relationships to seek out new business opportunities to leverage data science and advocate for team's skills; Effectively develop trust and collaboration with internal customers and cross-functional teams; Ensure alignment with IT support model, collaboration, tools and governance to enable data scientists to be most effective in executing their roles; Collaborate with other data science managers across the organization to establish high level strategy and optimize talent management</li><li>
20% Technical Exploration &amp; Development - Seek further knowledge on key developments within data science, technical skill sets, and additional data sources; Participate in the continuous improvement of data science and analytics by developing replicable solutions (for example, codified data products, project documentation, process flowcharts) to ensure solutions are leveraged for future projects; Ensure best practices and vision for data analysis and model productionalization are leveraged</li></ul> 
Direct Manager/Direct Reports:<ul><li>
This position typically reports to Senior Manager or above</li><li>
This position has Direct Reports &amp; manages programs</li></ul> 
Travel Requirements:<ul><li>
Typically requires overnight travel 5% to 20% of the time.</li></ul> 
Physical Requirements:<ul><li>
Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.</li></ul> 
Working Conditions:<ul><li>
Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.</li></ul> 
Minimum Qualifications:<ul><li>
Must be eighteen years of age or older.</li><li>
Must be legally permitted to work in the United States.</li></ul> 
Preferred Qualifications:<ul><li>
Bachelor&rsquo;s or Master&rsquo;s degree in Data Science, Computer Science, Engineering, Applied Mathematics, or a related technical field.</li><li>
7+ years of industry experience in data science, applied machine learning, or software engineering, and 2+ years in a people or technical leadership role.</li><li>
Strong foundation in applied data science with experience building and maintaining production-grade software, coupled with the ability to set technical direction, establish standards, and drive data science and engineering excellence from concept through production at scale.</li><li>
Hands-on experience developing AI-powered tools and platforms that integrate seamlessly with existing enterprise software ecosystems.</li><li>
Proficiency in python and solid understanding of engineering best practices, including APIs, microservices, version control, CI/CD, testing and deployment.</li><li>
Experience designing and operating large-scale data pipelines and distributed systems with AI/ML components, preferably on cloud platforms such as GCP and VertexAI.</li><li>
Familiar with microservices architectures and deploying models and APIs in containerized, cloud-neutral environments.</li><li>
Familiar with or contributed to AI agents or agentic applications in real-world, production settings.</li><li>
Proven ability to translate complex business processes and strategy into scalable, maintainable architectures, including well-orchestrated data and ML pipelines, while clearly communicating technical constraints and trade-offs to non-technical stakeholders.</li><li>
Domain experience in retail, merchandising, e-commerce, or supply chain, or familiarity in space intelligence concepts such as store layout optimization, merchandising analytics, computer vision, and LLM-based solutions.</li></ul> 
Minimum Education:<ul><li>
The knowledge, skills and abilities typically acquired through the completion of a bachelor's degree program or equivalent degree in a field of study related to the job.</li></ul> 
Preferred Education:<ul><li>
No additional education</li></ul> 
Minimum Years of Work Experience:<ul><li>
8</li></ul> 
Preferred Years of Work Experience:<ul><li>
No additional years of experience</li></ul> 
Minimum Leadership Experience:<ul><li>
None</li></ul> 
Preferred Leadership Experience:<ul><li>
None</li></ul> 
Certifications:<ul><li>
None</li></ul> 
Competencies:<ul><li>
Attracts Top Talent: Attracting and selecting the best talent to meet current and future business needs</li><li>
Builds Effective Teams: Building strong-identity teams that apply their diverse skills and perspectives to achieve common goals</li><li>
Builds Networks: Effectively building formal and informal relationship networks inside and outside the organization</li><li>
Business Insight: Applying knowledge of the business and the marketplace to advance the organization's goals</li><li>
Communicates Effectively: Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences</li><li>
Develops Talent: Developing people to meet both their career goals and the organization's goals</li><li>
Directs Work: Provides direction, delegating and removing obstacles to get work done</li><li>
Drives Engagement: Creating an environment where people are motivated to do their best to help the organization achieve its objectives</li><li>
Drives Vision and Purpose: Painting a compelling picture of the vision and strategy that motivates others to action</li><li>
Instills Trust: Gaining the confidence and trust of others through honesty, integrity, and authenticity</li><li>
Interpersonal Savvy: Relating openly and comfortably with diverse groups of people</li><li>
Organizational Savvy: Maneuvering comfortably through complex policy, process, and people-related organizational dynamics</li><li>
Persuades: Using compelling arguments to gain the support and commitment of others</li><li>
Strategic Mindset: Seeing ahead to future possibilities and translating them into breakthrough strategies</li></ul></div>

Data Science Manager - Space Planning Intelligence

Skylink Distributions (Pvt.) Ltd

The ideal candidate should have 3&ndash;4 years of professional experience in Data Analytics and Data Engineering, along with working experience in ERP systems, with proven hands-on expertise in building data pipelines, performing advanced analytics, integrating ERP data sources, and deploying scalable data solutions aligned with business objectives.Key ResponsibilitiesData Management &amp; Analysis<ul><li>Clean, pre-process, and validate large datasets to ensure accuracy, completeness, and consistency.</li><li>Handle missing values, outliers, and data inconsistencies using appropriate statistical techniques.</li><li>Conduct exploratory data analysis (EDA) using tools such as Python, R, SPSS, or other specialised statistical software.</li><li>Develop predictive and analytical models to solve business problems and improve decision-making.</li><li>Ensure adherence to data privacy regulations and internal governance standards.</li></ul>Data Visualization &amp; Reporting<ul><li>Create clear, impactful visualizations including dashboards, charts, and analytical reports.</li><li>Present findings and strategic insights to stakeholders in a clear and actionable manner.</li><li>Translate complex analytical results into business-friendly recommendations.</li></ul>Leadership &amp; Strategy<ul><li>Lead and mentor a team of data analysts and data scientists, fostering technical growth and professional development.</li><li>Provide guidance on best practices in modeling, feature engineering, and data validation.</li><li>Stay updated with the latest data science trends, tools, frameworks, and methodologies to continuously enhance team capabilities.</li><li>Define data science strategy aligned with organizational goals.</li></ul>Data Engineering &amp; Infrastructure Collaboration<ul><li>Manage and monitor data pipelines, ensuring data integrity, security, and performance.</li><li>Collaborate with data engineers to ensure seamless integration of data solutions within the company&rsquo;s infrastructure.</li><li>Oversee deployment, monitoring, and maintenance of machine learning models in production environments.</li></ul>Cross-Functional Collaboration<ul><li>Work closely with Research Teams, Clients, and Business Units to define project goals, KPIs, and deliverables.</li><li>Act as a bridge between technical teams and business stakeholders to ensure alignment.</li><li>Communicate project progress, risks, and outcomes effectively to leadership.</li></ul>ERP &amp; Business Intelligence Integration<ul><li>Lead integration of ERP systems with data science models and business intelligence platforms.</li><li>Ensure synchronisation between operational systems and analytical frameworks.</li><li>Align ERP-driven data workflows with predictive modeling and reporting tools to support strategic decision-making.</li></ul>Required Qualifications<ul><li>Bachelor&rsquo;s or Master&rsquo;s degree in Data Science, Computer Science, Statistics, Information Systems, or related field.</li><li>Strong expertise in Python, R, SQL, and statistical modeling techniques.</li><li>Experience with BI tools (e.g., Power BI, Tableau, or similar platforms).</li><li>Proven experience in managing data pipelines and model deployment.</li><li>Experience integrating ERP systems with analytics and BI tools.</li><li>Strong understanding of data governance, security, and compliance principles.</li></ul>Core Competencies<ul><li>Leadership and team management</li><li>Strategic thinking and business acumen</li><li>Advanced analytical and statistical skills</li></ul>Job Type: Full-timeWork Location: In person

Data Science Analyst

Bluevine

<div><div>About Bluevine

Bluevine is the largest small business banking platform in the U.S., redefining how entrepreneurs manage their money. We create modern financial solutions, from checking and lending to payments and beyond, designed to help small business owners grow, thrive, and take control of their financial future. Our best-in-class technology, advanced security, and deep understanding of the small business community give our customers the confidence to focus on what they do best.

Since 2013, we've supported more than 750,000 small businesses nationwide. Backed by leading investors like Lightspeed Venture Partners, Menlo Ventures, 83North, and Citi Ventures, our 500+ person global team shares one mission: to give small businesses the financial tools they need to succeed.

We're innovators driven by big ideas, collaboration, and real impact. Here, you'll have the freedom to take ownership, grow your career, and make a difference for small business owners across America. Ready to shape what's next?</div>
This is a hybrid role. At Bluevine, we pride ourselves on our collaborative culture, which we believe is best maintained through in-person interactions and a vibrant office environment. All of our offices have reopened in accordance with local guidelines, and are following a hybrid model. In-office days will be determined by location and discipline.

About the Role:

We are establishing a pioneering data science team in India and are seeking a highly skilled Data Science Manager to drive our efforts. In this role, you will lead a team of data scientists, guiding their work while also remaining hands-on with advanced data science tasks. You will play a crucial role in developing and implementing sophisticated models, coordinating with the group lead, and ensuring alignment with our strategic goals.

Key Responsibilities:
<ul>
<li>Team Leadership &amp; Development: Lead and mentor a team of 2 individual contributors (ICs), providing guidance on project execution, technical challenges, and professional growth. Foster a collaborative and innovative team environment.</li>
<li>Hands-on Modeling &amp; Analytics: Apply your expertise in advanced statistical, machine learning, and predictive modeling techniques to design, build, and improve decision-making systems. Set the standard for technical excellence within the team.</li>
<li>Project Management: Manage and oversee data science projects from concept to deployment, ensuring timely delivery of high-quality solutions. Allocate resources effectively and prioritize tasks to align with business objectives.</li>
<li>Stakeholder Communication: Serve as the primary point of contact between your team and the group lead. Communicate progress, challenges, and insights clearly and effectively, ensuring alignment with broader organizational goals.</li>
<li>MLOps &amp; System Integration: Lead efforts to maintain and enhance the data science infrastructure, integrating new technologies and practices into our workflows. Ensure that models are robust, scalable, and maintainable.</li>
<li>Strategic Data Collection: Oversee initiatives to develop and implement data collection strategies that support advanced analytics and model development. Ensure that data pipelines are efficient and reliable.</li>
</ul>
What We're Looking For:
<ul>
<li>7+ Years of Experience: A minimum of 7 years of experience in data science, with at least 2 years in a leadership or managerial role. Demonstrated experience in leading teams and delivering complex data-driven solutions.</li>
<li>Expertise in Python: Extensive experience in developing and deploying production-level code in Python, with a deep understanding of machine learning frameworks such as Scikit-learn, PyTorch, TensorFlow, or similar.</li>
<li>Strong SQL and Database Knowledge: Proficiency in working with relational databases, writing optimized SQL queries, and managing large-scale datasets.</li>
<li>Comprehensive ML Lifecycle Experience: Proven ability to manage the entire lifecycle of ML model development, from ideation and experimentation to deployment and monitoring in a production environment.</li>
<li>Analytical &amp; Strategic Thinking: Ability to analyze complex data sets, derive actionable insights, and communicate these insights effectively to both technical and non-technical stakeholders.</li>
<li>Educational Background: A Master's or Ph.D. in Statistics, Computer Science, Engineering, or a related quantitative field is preferred.</li>
<li>Proven Leadership Skills: Demonstrated ability to lead a team, manage multiple priorities, and work effectively across functions and geographies.</li>
</ul>
Bonus Points:
<ul>
<li>Cross-Functional Collaboration: Experience working with Data/MLOps Engineering, Analytics, Business, and Product teams in a collaborative environment.</li>
<li>Domain Specialization: Expertise in areas like fraud detection, credit risk prediction, or graph models and analytics.</li>
<li>MLOps &amp; Cloud Infrastructure: Hands-on experience with MLOps, particularly within the AWS ecosystem, and familiarity with orchestration tools like Apache Airflow.</li>
<li>Experimentation &amp; Impact Analysis: Skilled in designing experiments and analyzing their outcomes to measure the impact and effectiveness of data-driven solutions.</li>
</ul><div>
Benefits &amp; Perks
<ul>
<li>Excellent group health coverage and life insurance</li>
<li>Stock options</li>
<li>Hybrid work model</li>
<li>Meal allowance</li>
<li>Transportation assistance (terms and conditions apply)</li>
<li>Generous paid time off plan, Holidays</li>
<li>Company-sponsored mental health benefits</li>
<li>Financial advisory services for both short- and long-term goals</li>
<li>Learning and development opportunities to support career growth</li>
<li>Community-based volunteering opportunities</li></ul></div></div>

Manager, Data Science

Information Technology Senior Management Forum

<div><div>Posted Date
2/20/2026
</div><div>Description
<div>Manager, Data Analysis
At Capital One, data is at the center of everything we do. When we launched 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.
We are looking for a high performing and motivated manager to help us on our transformation journey to modernize our compliance testing script management. The candidate will have the ability to set the script intent for the new automated process, develop change management process, and drive governance to ensure our testing community will always have access to the accurate and up-to-date data. The person will have the opportunity to work across various teams, from the data analyst, second line testing team, product management, to the tech team in developing and implementing the solution.
What you&rsquo;ll do:<ul><li>
Drive current and future strategy by leveraging your analytical skills</li><li>
Assist with building and developing new tools and processes to strengthen the compliance testing</li><li>
Work with vast amounts of data in new and evolving environments</li><li>
Be a part of growing and developing our brand in the testing products</li><li>
Leverage analytics to create a customer experience above our peers</li><li>
Lead a team of talented junior analysts on an exciting professional journey while mentoring them and elevating their careers</li><li>
Be a part of the full life cycle of projects and see end results</li><li>
Collaborate across business units</li><li>
Work with top talent in a fast paced, entrepreneurial environment where analytics and good data are a top priority</li><li>
Experience real work life balance, with little travel involved</li></ul> 
On any given day you will be:<ul><li>
 Identifying, developing, improving and implementing process, data, and reporting improvements for the organization</li><li>
Working with large and complex databases containing millions to billions of records</li><li>
Improving operational efficiencies and effectiveness</li><li>
Conducting analysis to evaluate processes and tests</li><li>
Extracting and analyzing data to enhance the the testing product</li></ul>
An ideal candidate will be on the leading edge of Analytical technology with a passion for the newest and most innovative tools. Possessing strong problem solving and conceptual thinking abilities in addition to communication, interpersonal and leadership skills are also important. This position will be in a fast-paced and entrepreneurial environment where you will be handling multiple concurrent projects while working independently and in teams. This role will have a strong process, operation, and governance components and those with a operational background are strongly encouraged to apply.
Basic Qualifications<ul><li>
Currently has, or is in the process of obtaining a Bachelor&rsquo;s Degree in quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science or a related quantitative field) plus at least 6 years of experience performing data analytics, or currently has, or is in the process of obtaining a Master&rsquo;s Degree plus at least 4 years of experience performing data analytics with an expectation that required degree will be obtained on or before the scheduled start date.</li><li>
At least 4 years of experience performing professional data analysis work</li><li>
At least 4 years of experience performing programming</li></ul>
Preferred Qualifications:<ul><li>
Master&rsquo;s Degree in a Science, Technology, Engineering, Mathematics discipline</li><li>
At least 7 years of professional data analysis work experience</li><li>
At least 4 years of experience with Python, R, Spark or SQL</li><li>
At least 1 year of experience in people management</li><li>
At least 1 years of project management experience</li><li>
At least 1 year of experience in Tableau</li><li>
Proficient utilizing and developing within AWS service</li></ul> 
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: $164,800 - $188,100 for Data Analysis Manager 

Richmond, VA: $149,800 - $171,000 for Data Analysis Manager 
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&rsquo;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 the Capital 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&rsquo;s Fair Chance Act; Philadelphia&rsquo;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).
Manager, Data Analysis
At Capital One, data is at the center of everything we do. When we launched 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.
We are looking for a high performing and motivated manager to help us on our transformation journey to modernize our compliance testing script management. The candidate will have the ability to set the script intent for the new automated process, develop change management process, and drive governance to ensure our testing community will always have access to the accurate and up-to-date data. The person will have the opportunity to work across various teams, from the data analyst, second line testing team, product management, to the tech team in developing and implementing the solution.
What you&rsquo;ll do:<ul><li>
Drive current and future strategy by leveraging your analytical skills</li><li>
Assist with building and developing new tools and processes to strengthen the compliance testing</li><li>
Work with vast amounts of data in new and evolving environments</li><li>
Be a part of growing and developing our brand in the testing products</li><li>
Leverage analytics to create a customer experience above our peers</li><li>
Lead a team of talented junior analysts on an exciting professional journey while mentoring them and elevating their careers</li><li>
Be a part of the full life cycle of projects and see end results</li><li>
Collaborate across business units</li><li>
Work with top talent in a fast paced, entrepreneurial environment where analytics and good data are a top priority</li><li>
Experience real work life balance, with little travel involved</li></ul> 
On any given day you will be:<ul><li>
 Identifying, developing, improving and implementing process, data, and reporting improvements for the organization</li><li>
Working with large and complex databases containing millions to billions of records</li><li>
Improving operational efficiencies and effectiveness</li><li>
Conducting analysis to evaluate processes and tests</li><li>
Extracting and analyzing data to enhance the the testing product</li></ul>
An ideal candidate will be on the leading edge of Analytical technology with a passion for the newest and most innovative tools. Possessing strong problem solving and conceptual thinking abilities in addition to communication, interpersonal and leadership skills are also important. This position will be in a fast-paced and entrepreneurial environment where you will be handling multiple concurrent projects while working independently and in teams. This role will have a strong process, operation, and governance components and those with a operational background are strongly encouraged to apply.
Basic Qualifications<ul><li>
Currently has, or is in the process of obtaining a Bachelor&rsquo;s Degree in quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science or a related quantitative field) plus at least 6 years of experience performing data analytics, or currently has, or is in the process of obtaining a Master&rsquo;s Degree plus at least 4 years of experience performing data analytics with an expectation that required degree will be obtained on or before the scheduled start date.</li><li>
At least 4 years of experience performing professional data analysis work</li><li>
At least 4 years of experience performing programming</li></ul>
Preferred Qualifications:<ul><li>
Master&rsquo;s Degree in a Science, Technology, Engineering, Mathematics discipline</li><li>
At least 7 years of professional data analysis work experience</li><li>
At least 4 years of experience with Python, R, Spark or SQL</li><li>
At least 1 year of experience in people management</li><li>
At least 1 years of project management experience</li><li>
At least 1 year of experience in Tableau</li><li>
Proficient utilizing and developing within AWS service</li></ul> 
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: $164,800 - $188,100 for Data Analysis Manager 

Richmond, VA: $149,800 - $171,000 for Data Analysis Manager 
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&rsquo;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 the Capital 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&rsquo;s Fair Chance Act; Philadelphia&rsquo;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).</div>
</div><div>Salary
164,800.00 - 188,100.00 Annual
</div><div></div><div><div>Type<div>
Full-time</div></div></div></div>

Manager, Data Analysis

Finaira

<div>The Principal Data Scientist will provide strategic technical leadership and direction for data science initiatives across the organization, particularly within the financial sector. This role is responsible for driving innovation, setting technical standards, mentoring a team of data scientists, and collaborating with senior stakeholders to define and deliver high-impact AI and machine learning solutions that align with business strategy and drive significant value.
The difference you will make:<ul><li>
Define the technical data science strategy and roadmap.</li><li>
Lead the research and development of cutting-edge AI solutions.</li><li>
Evaluate and implement new data science technologies and platforms.</li><li>
Provide technical leadership and guidance to the data science team.</li><li>
Ensure the scalability and reliability of data science infrastructure.</li></ul> 

Requirements 
Education:
<ul><li>Master&rsquo;s degree or Ph.D. in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field with an exceptional academic record.</li></ul>
Experience:<ul><li>
8+ years of progressive experience in data science, with more than 2 years spent leading and successfully delivering complex AI/ML projects with demonstrable business impact.</li><li>
Extensive and deep experience in the financial services industry, with a comprehensive understanding of financial data, regulations, and business challenges.
</li><li>Proven experience in leading and mentoring data science teams.
</li><li>A strong portfolio showcasing the successful application of AI/ML to solve significant financial problems (e.g., transformative fraud prevention systems, advanced risk management platforms, high-impact algorithmic trading strategies, game-changing customer analytics solutions)</li></ul>
Technical Skills:
<ul><li>Expert-level mastery in multiple programming languages relevant to data science (e.g., Python, R, Scala, Java) and their associated libraries and frameworks.</li><li>
Deep and comprehensive expertise across a wide range of machine learning frameworks, including advanced knowledge of deep learning architectures and specialized tools.</li><li>
Exceptional understanding of both foundational and cutting-edge statistical concepts and ML algorithms, including deep learning architecture and specialized tools.</li><li>
Deep understanding of Data and AI governance frameworks and requirements.
</li><li>Advanced mathematical skills, demonstrating a strong theoretical understanding and practical application to complex financial problems.
</li><li>Expert-level proficiency in SQL and a variety of database management systems (both relational and NoSQL), with the ability to design and optimize data storage and retrieval for large-scale AI/ML applications.</li><li>
Extensive experience with advanced data visualization tools and the ability to communicate complex insights to executive audiences through compelling visuals and narratives.
</li><li>Deep and practical experience with cloud computing platforms (AWS, Azure, GCP) and their comprehensive suite of AI/ML services, including architecting and deploying scalable solutions.
</li><li>Proven expertise in designing and working with large, complex data sets and big data technologies (Hadoop, Spark, etc.), including the ability to optimize data processing workflows for performance and scalability.
</li><li>Mastery of various distributed databases (Hive, Impala, Redis, etc.) and a proven ability to design and implement efficient data storage and access patterns for AI/ML workloads.</li></ul>
Soft Skills:<ul><li>
Strong ownership and accountability for assigned work.
</li><li>Clear and professional verbal and written communication.</li><li>
Effective time management and task prioritization.</li><li>
Analytical thinking and problem-solving skills.</li><li>
Ability to work independently, collaborate effectively and mentor junior team members.</li><li>
Ability to actively listen to customers and accurately understand their needs, expectations, and challenges.</li><li>
Adaptability and learning agility in a fast-paced environment.</li><li>
Strong attention to detail and a commitment to quality.</li><li>
Receptiveness to feedback and continuous improvement mindset.</li></ul>
Finaira is an Equal Opportunity Employer and is committed to providing a workplace free of discrimination and harassment. All employment decisions are based on business needs, job requirements, and individual qualifications, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other status protected by the laws or regulations in the locations where we operate.</div>

Principal Data Scientist

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