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Data Engineer, Product Analytics

Amazon Web Services (AWS)

<div>
 
 Description
 
 
 
 Amazon Quick Suite is an enterprise AI platform that transforms how organizations work with their data and knowledge. Combining generative AI-powered search, deep research capabilities, intelligent agents and automations, and comprehensive business intelligence, Quick Suite serves tens of thousands of users. Our platform processes thousands of queries monthly, helping teams make faster, data-driven decisions while maintaining enterprise-grade security and governance. From natural language interactions with complex datasets to automated workflows and custom AI agents, Quick Suite is redefining workplace productivity at unprecedented scale.
 
 
 We are seeking a Data Scientist II to join our Quick Data team, focusing on evaluation and benchmarking data development for Quick Suite features, with particular emphasis on Research and other generative AI capabilities. Our mission is to engineer high-quality datasets that are essential to the success of Amazon Quick Suite. From human evaluations and Responsible AI safeguards to Retrieval-Augmented Generation and beyond, our work ensures that Generative AI is enterprise-ready, safe, and effective for users at scale.
 
 
 As part of our diverse team&mdash;including data scientists, engineers, language engineers, linguists, and program managers&mdash;you will collaborate closely with science, engineering, and product teams. We are driven by customer obsession and a commitment to excellence.
 
 
 Key job responsibilities
 
 
 In this role, you will leverage data-centric AI principles to assess the impact of data on model performance and the broader machine learning pipeline. You will apply Generative AI techniques to evaluate how well our data represents human language and conduct experiments to measure downstream interactions.
 
 
 
 Specific Responsibilities Include
 
 
 
 <ul>
 <li>
 Design and develop comprehensive evaluation and benchmarking datasets for Quick Suite AI-powered features
 </li>
 <li>
 Leverage LLMs for synthetic data corpora generation; data evaluation and quality assessment using LLM-as-a-judge settings
 </li>
 <li>
 Create ground truth datasets with high-quality question-answer pairs across diverse domains and use cases
 </li>
 <li>
 Lead human annotation initiatives and model evaluation audits to ensure data quality and relevance
 </li>
 <li>
 Develop and refine annotation guidelines and quality frameworks for evaluation tasks
 </li>
 <li>
 Conduct statistical analysis to measure model performance, identify failure patterns, and guide improvement strategies
 </li>
 <li>
 Collaborate with ML scientists and engineers to translate evaluation insights into actionable product improvements
 </li>
 <li>
 Build scalable data pipelines and tools to support continuous evaluation and benchmarking efforts
 </li>
 <li>
 Contribute to Responsible AI initiatives by developing safety and fairness evaluation datasets
 
 
 </li>
 </ul>
 
 About The Team
 
 
 
 Why AWS?
 
 
 Amazon Web Services (AWS) is the world&rsquo;s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating &mdash; that&rsquo;s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
 
 
 Inclusive Team Culture
 
 
 Here at AWS, it&rsquo;s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness.
 
 
 Mentorship &amp; Career Growth
 
 
 We&rsquo;re continuously raising our performance bar as we strive to become Earth&rsquo;s Best Employer. That&rsquo;s why you&rsquo;ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
 
 
 Work/Life Balance
 
 
 We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there&rsquo;s nothing we can&rsquo;t achieve in the cloud.
 
 
 Hybrid Work
 
 
 We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.
 
 
 
 Basic Qualifications
 
 
 
 <ul>
 <li>
 2+ years of data scientist experience
 </li>
 <li>
 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
 </li>
 <li>
 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
 </li>
 <li>
 1+ years of working with or evaluating AI systems experience
 </li>
 <li>
 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
 </li>
 <li>
 Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
 </li>
 <li>
 Experience applying theoretical models in an applied environment
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
 </li>
 <li>
 Knowledge of machine learning concepts and their application to reasoning and problem-solving
 </li>
 <li>
 Experience in a ML or data scientist role with a large technology company
 </li>
 <li>
 Experience in defining and creating benchmarks for assessing GenAI model performance
 </li>
 <li>
 Experience working on multi-team, cross-disciplinary projects
 </li>
 <li>
 Experience applying quantitative analysis to solve business problems and making data-driven business decisions
 </li>
 <li>
 Experience effectively communicating complex concepts through written and verbal communication
 
 
 </li>
 </ul>
 Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
 
 
 Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
 
 
 Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.
 
 
 The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
 
 
 USA, CA, Santa Clara - 157,300.00 - 212,800.00 USD annually
 
 
 USA, NY, New York - 153,400.00 - 207,500.00 USD annually
 
 
 USA, WA, Seattle - 136,000.00 - 184,000.00 USD annually
 
 
 
 
 Company
 
 - Amazon Development Center U.S., Inc.
 
 
 Job ID: A10411927
</div>

Data Scientist, AWS Quick Data

Spotify

<div>
 We are looking for a Data Scientist to join the Business Analytics team at Spotify. In this role, you&rsquo;ll shape Spotify&rsquo;s performance marketing and growth strategy by developing models, designing experiments and measuring the impact of marketing investments. Partnering with the Growth Analytics Lead, you&rsquo;ll turn data into strategies that guide budget allocation, optimize spend and accelerate efficient growth across paid media channels. You&rsquo;ll collaborate with a global, cross-functional team of analysts, data scientists, marketers, business leaders, and engineers to scale insights and drive efficient growth. Learning and improving is part of our daily routine, and you will get a platform to develop your data skills and carve out efficient ways of working.
 
 
 The Business Analytics team is part of Spotify&rsquo;s core business strategy organization. You&rsquo;ll play a crucial role in the growth and direction of Spotify as we grow to 700M+ users around the globe. At your fingertips, you&rsquo;ll have access to all of the data Spotify has to offer, and the opportunity to be creative with how you use it to derive insights and strategies. Above all, your work will impact the way the world experiences audio!
 
 
 What You'll Do
 
 
 <ul>
 <li>
 Develop data-driven strategies to drive the growth of Spotify users and subscribers, with a focus on performance marketing
 </li>
 <li>
 Refine attribution practices and define robust, data-backed methods to measure the incremental impact of marketing spend
 </li>
 <li>
 Partner with third-party advertising platforms and agencies to design and implement comprehensive experiments and lift studies
 </li>
 <li>
 Contribute to annual and quarterly planning through impact forecasting, budget allocation and scenario modelling
 </li>
 <li>
 Build scalable data pipelines and dashboards to track marketing efficiency and Global business performance
 </li>
 <li>
 Collaborate closely with business partners to understand growth drivers and guide strategic marketing decisions
 </li>
 <li>
 Present insights and recommendations to senior stakeholders, influencing the course of our business
 
 
 </li>
 </ul>
 Who You Are
 
 
 <ul>
 <li>
 3+ years synthesizing insights from data using tools such as Python/R and SQL
 </li>
 <li>
 Hands-on experience supporting marketing organizations with their paid media strategy, including running and analyzing incrementality tests on platforms like Meta, Google and TikTok
 </li>
 <li>
 Proven experience building advanced models to understand and optimise paid media campaigns
 </li>
 <li>
 Skilled at collaborating with business partners to measure the impact of marketing initiatives and presenting those findings in coherent recommendations
 </li>
 <li>
 Intellectually curious, creative, and diligent - you enjoy thinking about the business as much as about the data
 </li>
 <li>
 Have a background in Computer Science, Statistics, Engineering or other relevant field
 </li>
 <li>
 Comfortable working on a globally distributed team (with occasional international travel)
 
 
 </li>
 </ul>
 Where You'll Be
 
 
 <ul>
 <li>
 This role is based in New York
 </li>
 <li>
 We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.
 
 
 </li>
 </ul>
 The United States base range for this position is $110,018 - $157,169, plus equity. The benefits available for this position include health insurance, six month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, paid flexible holidays, paid sick leave. These ranges may be modified in the future.
 
 
 Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what&rsquo;s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It&rsquo;s in our differences that we will find the power to keep revolutionizing the way the world listens.
 
 
 At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we&rsquo;re here to support you in any way we can.
 
 
 Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world&rsquo;s most popular audio streaming subscription service.
</div>

Data Scientist - Growth Analytics (Performance Marketing)

Ventas, Inc.

<div>
 
 Job Description
 
 
 
 Ventas is a leading S&amp;P 500 company enabling exceptional environments that benefit a large and growing aging population. With an enterprise value exceeding $50 billion and a portfolio of more than 1,400 properties across North America and the United Kingdom, Ventas is a preeminent participant in the longevity economy. Its largest business is private-pay senior housing, which includes over 850 communities providing valuable care and services to more than 90,000 residents. The Ventas portfolio also includes outpatient medical buildings, research centers and healthcare facilities that attract strong institutional demand from the largest health systems, biomedical companies and universities and other research institutions in the world. Backed by strong financial performance and a collaborative culture, Ventas has the capital, capabilities and relationships to deliver superior value. The experienced Ventas team shares a commitment to each other and to the Company&rsquo;s mission of helping people live longer, healthier, happier lives.
 
 
 The Data Science team partners across Ventas to translate complex data into actionable insights that support investment, operational, and strategic decisions. Through advanced analytics and predictive modeling, the team helps uncover performance drivers, anticipate future outcomes, and enable stronger, data‑driven decision‑making across our Senior Housing portfolio.
 
 
 
 About The Role
 
 
 
 The Analyst, Data Science role offers a unique opportunity at an S&amp;P 500 company to apply analytical thinking and technical skills to drive core business outcomes for Ventas&rsquo; Senior Housing portfolio, with direct partnerships with finance, operations, portfolio management, and enterprise strategy. Key responsibilities include:
 
 
 <ul>
 <li>
 Explore, engineer, and derive analytical features from large, complex datasets to surface meaningful signals and drivers of business performance
 </li>
 <li>
 Perform diagnostic and exploratory analyses to identify correlations, patterns, and relationships across financial, operational, and portfolio‑level data
 </li>
 <li>
 Develop analytical frameworks to understand key business levers and quantify their impact on outcomes such as revenue, occupancy, rate, and mix
 </li>
 <li>
 Build and refine predictive models and scenario analyses to anticipate future performance and support proactive decision‑making
 </li>
 <li>
 Translate ambiguous business questions into well‑structured analytical problems and deliver clear, actionable insights to stakeholders
 </li>
 <li>
 Partner closely with teams across finance, operations, portfolio management, and strategy to align analytics with real‑world business decisions
 </li>
 <li>
 Communicate findings through compelling data visualizations, dashboards, and executive‑ready narratives that drive action
 </li>
 <li>
 Continuously evaluate data quality and model performance, recommending improvements to strengthen analytical rigor and reliability
 </li>
 <li>
 Contribute to the evolution of analytics best practices and serve as a thought partner to colleagues on analytical approaches and interpretation
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Data Science, Computer Science, Mathematics, Engineering, Statistics, or a related field. Master&rsquo;s degree preferred.
 </li>
 <li>
 2+ years of experience in a related analytical field (data analytics, data science, consulting, or similar), with demonstrated experience solving complex, ambiguous problems using data.
 </li>
 <li>
 Must be located in the New York City, NY surrounding area willing to relocate for the duration of employment.
 </li>
 <li>
 Willingness to adapt and thrive in a blended work environment with 3-days in office, seamlessly transitioning between remote work and in-office operations.
 </li>
 <li>
 Proficiency in SQL and Python required.
 </li>
 <li>
 Experience translating ambiguous business questions to analytical problems
 </li>
 <li>
 Strong analytical, problem‑solving, and communication skills with the ability to explain complex information clearly.
 </li>
 <li>
 Ability to manage multiple priorities in a fast‑paced, collaborative, and lean environment.
 </li>
 <li>
 Must be legally authorized to work in the United States without the need for employer sponsorship now or in the future.
 
 
 </li>
 </ul>
 
 The estimated base salary range for this position is $80,000 &ndash; $105,000 per year. This range reflects a good-faith estimate of the base salary Ventas reasonably expects to pay at the time of posting. Actual base pay will be determined based on work location, skills, qualifications, relevant experience, and business needs.
 
 
 
 
 In addition to base salary, this role is eligible for discretionary incentive compensation and a comprehensive benefits package, which includes medical, dental, vision, retirement savings, paid time off, and other wellness benefits under applicable plan terms.
 
 
 
 Ventas, Inc. offers a competitive compensation and benefits package to the successful candidate.
 
 
 Ventas, Inc. is an Equal Opportunity Employer.
 
 
 Ventas, Inc. does not accept unsolicited resumes from staffing agencies, search firms or any third parties.
 
 
</div>

Analyst, Data Science

MatchPoint

<div>
 
 MatchPoint Solutions is a fast-growing, young, energetic global IT-Engineering services company with clients across the US. We provide technology solutions to various clients like
 
 Uber, Robinhood, Netflix, Airbnb, Google, Sephora, and more!
 
 More recently, we have expanded to working internationally in
 
 Canada, China, Ireland, UK, Brazil, and India
 
 . Through our culture of innovation, we inspire, build, and deliver business results, from ideas to outcome. We keep our clients on the cutting edge of the latest technologies and provide solutions by using industry-specific best practices and expertise.
 
 
 
 
 
 We are excited to be continuously expanding our team. If you are interested in this position, please send over your updated resume. We look forward to hearing from you!
 
 
 
 
 
 
 Job Title: Data Scientist -Growth Analytics
 
 
 
 
 Location: New York City, NY (Hybrid-3 days a week)
 
 
 
 
 Employment Type: Fulltime
 
 
 
 
 
 
 
 
 
 
 
 Responsibilities Growth Strategy &amp; Acquisition
 
 
 <ul>
 <li>
 
 Pricing &amp; Incentive Strategy:
 
 Design and test dynamic pricing models and incentive structures (e.g., first-order discounts, owner bonuses). You will mathematically determine how to stoke demand and aid conversion without eroding our contribution profit margins, ensuring every dollar of "discount" generates long-term ROI.
 </li>
 <li>
 
 The Growth Equation:
 
 Model our acquisition channels (Organic, Paid, Referral, Ambassadors). You will identify which channels have the highest LTV/CAC ratio and tell us where to double down.
 </li>
 <li>
 
 Viral Loops:
 
 Analyze our referral and sharing behaviors. You will calculate our K-factor (virality) and identify product changes to keep our users as our best marketing channel.
 </li>
 </ul>
 
 
 
 
 
 Marketplace Liquidity &amp; Retention
 
 
 <ul>
 <li>
 
 Supply-Led Growth:
 
 Analyze how inventory levels drive organic growth. Does adding 100 power owners in Chicago unlock 1,000 new customers? You will tell us where to focus supply acquisition.
 </li>
 <li>
 
 The "Magic Moments":
 
 Identify the specific user behaviors that lead to long-term retention (e.g., "Users who rent within 7 days of signup retain at 3x").
 </li>
 <li>
 
 Churn Prediction:
 
 Build models to identify at-risk users before they leave, allowing our CX team to intervene.
 </li>
 </ul>
 
 
 
 
 
 Product Conversion (CRO)
 
 
 <ul>
 <li>
 
 Funnel Optimization:
 
 Own the granular analysis of our demand and supply funnels. You will find the leaks in the bucket and design A/B tests to plug them.
 </li>
 <li>
 
 Experimentation:
 
 Help the product team design valid experiments. You ensure we aren't just shipping features, but moving metrics with statistical significance.
 </li>
 </ul>
 
 
 
 
 
 Requirements
 
 
 <ul>
 <li>
 
 The "Grinder" Mentality:
 
 You are relentlessly curious. You are the type of person who can't put something down until you figure out the why.
 </li>
 <li>
 
 Growth Native:
 
 You speak the language of growth: CAC, LTV, ROAS, K-Factor, Churn, and Cohorts. You understand that "Data Science" is a tool to make money and grow the user base.
 </li>
 <li>
 
 Product Fluency:
 
 You understand product growth loops and can quickly execute and extract insights from demand funnels and A/B tests
 </li>
 <li>
 
 5+ Years Experience:
 
 Ideally in a Consumer Marketplace or high-growth B2C app. You have seen how a company scales and understand the data infrastructure needed to support it.
 </li>
 <li>
 
 Note:
 
 We are open to less experience if you have exceptional raw talent and a portfolio of solving complex growth problems.
 </li>
 <li>
 
 Technical Fluency:
 
 Expert-level SQL. Proficient in Python/R for modeling. Experience with growth stacks (PostHog, Mixpanel, AppsFlyer, Segment) and visualization tools.
 </li>
 </ul>
 
 
 
 
 
 
 
 MatchPoint Solutions provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
 
 
 
 
 
 This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.
 
</div>

Data Scientist with Growth Analytics

Andiamo

<div>
 
 About The Role
 
 
 
 When you work in this role, you&rsquo;ll tackle tough problems alongside other scientists and engineers&mdash;people who will challenge your ideas, share knowledge, and collaborate on impactful projects. You&rsquo;ll be doing work that matters, developing solutions to complex real-world problems using data, invention, and rigorous inquiry.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Independently research and develop hypotheses based on diverse real-world datasets.
 </li>
 <li>
 Conduct literature reviews to apply cutting-edge methodologies for extracting meaningful signals from data.
 </li>
 <li>
 Partner with engineers and stakeholders to rigorously explore and test your theories.
 </li>
 <li>
 Stay engaged in the academic community by joining reading circles and attending seminars to keep up with the latest research.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 1&ndash;5+ years of experience in applied data analysis and prediction, preferably in an industry setting.
 </li>
 <li>
 Degree in a technical or quantitative discipline such as statistics, mathematics, physics, electrical engineering, or computer science.
 </li>
 <li>
 Proficiency in Python and SQL.
 </li>
 <li>
 Experience conducting in-depth research projects involving real-world data.
 </li>
 <li>
 Ability to think independently, approach analysis creatively, and communicate complex ideas clearly.
 </li>
 <li>
 Background in finance is not required&mdash;strong research skills are most important.
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 <ul>
 <li>
 Core Benefits: Fully paid medical and dental insurance premiums for employees and dependents, competitive 401k match, employer-paid life and disability insurance.
 </li>
 <li>
 Perks: Onsite gyms with laundry service, wellness activities, casual dress, snacks, game rooms.
 </li>
 <li>
 Learning: Tuition reimbursement, conference and training sponsorship.
 </li>
 <li>
 Time Off: Generous vacation and unlimited sick days, competitive paid caregiver leaves.
 </li>
 <li>
 Hybrid Work Policy: Flexible in-office days with budget for home office setup.
 
 
 </li>
 </ul>
 
 Compensation
 
 
 
 The base pay for this role will be between
 
 $165,000 and $300,000
 
 . This role may also be eligible for additional forms of compensation and benefits such as discretionary bonuses, health and wellness plans, and 401(k) contributions. Discretionary bonus can be a significant portion of total compensation. Actual compensation will depend on skills, qualifications, and experience.
 
 
 
 About Andiamo
 
 
 
 Talent Partners for the AI Revolution. As a globally recognized staffing and consulting firm, we specialize in placing the top 2% of technology and go-to-market professionals with the world&rsquo;s largest and most well-known companies.
 
 
 For over 20 years, we've maintained the status of tier-one vendor for firms such as Palantir, Amazon, Fluidstack, Bloomberg, Relativity Space, Firefly, MasterCard, Visa, Two Sigma, Citadel, as well as other major financial services firms, elite hedge funds, Google-backed tech start-ups, and major software firms.
 
 
 Our talent solutions include Permanent Placement, Contract Staffing, Executive Search, and Dedicated Recruiting Services (RPO). Find out more at www.andiamogo.com
</div>

Data Scientist

Bank of America

<div>
 
 Job Description:
 
 
 
 At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day.
 
 
 Being a Great Place to Work is core to how we drive Responsible Growth. This includes our commitment to being an inclusive workplace, attracting and developing exceptional talent, supporting our teammates&rsquo; physical, emotional, and financial wellness, recognizing and rewarding performance, and how we make an impact in the communities we serve.
 
 
 Bank of America is committed to an in-office culture with specific requirements for office-based attendance and which allows for an appropriate level of flexibility for our teammates and businesses based on role-specific considerations.
 
 
 At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!
 
 
 
 The Data and AI team within Global Payment Solutions (GPS) at Bank of America
 
 is looking for a highly technical Research Engineer that is a self-starter who can translate complex concepts and generate actionable insights.
 
 
 
 Who we are:
 
 
 
 The GPS Data and AI team drives and powers innovation within the one of the largest payment businesses in the world. We are the core data scientists building end-to-end production level solutions at scale. The team is a collection of individuals that welcomes challenging problems because that is where the learning begins. Many of our projects begin with &ldquo;think tank&rdquo; sessions with business teams that is later translated to tangible solutions and products.
 
 
 
 Representative Projects:
 
 
 
 <ul>
 <li>
 Develop advanced statistical methods to determine the optimal interest-rate or product pricing strategies for clients
 </li>
 <li>
 Build a Generative AI-powered search platform that enables sales and product teams to access high quality answers to product, servicing, and client related questions
 </li>
 <li>
 Develop AI models that shift foreign currency conversion &ldquo;up the payment stream,&rdquo; reducing reliability on beneficiary banks
 </li>
 <li>
 Apply advanced NLP techniques to generate near real-time insights into what clients are reaching out to servicing teams about, helping servicing teams anticipate client needs and improve service quality
 
 
 </li>
 </ul>
 
 Who we&rsquo;re looking for:
 
 
 
 As a Research Engineer on the GPS team, you will tackle one of our most import challenges: building models that transform data into revenue-driving insights and products. This role blends research, engineering, and product responsibilities, requiring you to design statistical models, build scalable ML pipelines, and deploy algorithms directly into our production systems. You will work across teams to solve problems in recommendation, stochastic optimization, and time-series forecasting; while running large A/B tests on new methods we design to push the boundaries of what data can achieve.
 
 
 If you are passionate about working in cross-functional teams and utilizing your skills for technical product management, statistical analytics, predictive modeling, and generating revenue, consider applying to this role.
 
 
 
 Responsibilities:
 
 
 
 <ul>
 <li>
 Frame abstract business problems using advanced data science and machine learning algorithms
 </li>
 <li>
 Work with stakeholders throughout the organization to identify opportunities for leveraging internal and external data to drive business solutions
 </li>
 <li>
 Own critical research and application development, strengthening the firm's competitive advantage
 </li>
 <li>
 Shape cross-team collaboration to advance the firm's data science capabilities
 
 
 </li>
 </ul>
 
 Required Skills:
 
 
 
 <ul>
 <li>
 Minimum Bachelor&rsquo;s degree in a quantitative field such as computer science, math, statistics, and physics
 </li>
 <li>
 Minimum 3 years of experience with translating mathematical models and algorithms into code (Python and/or C++)
 </li>
 <li>
 Strong foundation in probability, statistics, and applied machine learning (NLP, time-series analysis, Generative AI)
 </li>
 <li>
 Prior experience working in a highly technical data driven research environment
 </li>
 <li>
 Ability to communicate complex topics in a concise and coherent manner
 
 
 </li>
 </ul>
 
 Desired Skills:
 
 
 
 <ul>
 <li>
 Graduate level degree in a quantitative field such as, computer science, math, statistics, and physics
 </li>
 <li>
 Demonstrated prior experience through work, research or passion projects in RAG, Agentic Frameworks, LLMs, Reinforcement Learning
 </li>
 <li>
 Are energized by the high stakes and intensity of dynamic environments and ready to dive in whenever
 </li>
 <li>
 Are excited to dive into new technical areas on a regular basis
 
 
 </li>
 </ul>
 
 Shift:
 
 
 
 1st shift (United States of America)
 
 
 
 Hours Per Week:
 
 
 
 40
</div>

Data Scientist I

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