ml scientist

A.P. Moller - Maersk

<div>
 
 AI/ML Scientist (Operations research/Optimization/Simulation)
 
 
 
 
 A.P. Moller - Maersk
 
 
 
 A.P. Moller &ndash; Maersk is the global leader in container shipping services. The business operates in 130 countries and employs 80,000 staff. An integrated container logistics company, Maersk aims to connect and simplify its customers&rsquo; supply chains.
 
 
 Today, we have more than 180 nationalities represented in our workforce across 131 Countries and this mean, we have elevated level of responsibility to continue to build inclusive workforce that is truly representative of our customers and their customers and our vendor partners too.
 
 
 The team - who are we:
 
 
 We are an ambitious team with the shared passion to use data, data science (DS), machine learning (ML), advanced simulation, optimization and engineering excellence to make a difference for our customers.
 
 
 We are a team, not a collection of individuals. We value our diverse backgrounds, our different personalities and strengths &amp; weaknesses. We value trust and passionate debates. We challenge each other and hold each other accountable. We uphold a caring feedback culture to help each other grow, professionally and personally.
 
 
 We are now seeking a new team member who is excited about developing advanced simulation models,optimization algorithms and AI/ML solutions that create operational insights for container shipping terminals
 
 
 worldwide, helping them optimize container handling, yard operations, vessel operations, and drive efficiency
 
 
 and business value.
 
 
 We Offer - This Is What You Get
 
 
 You will be part of the APM Terminals team within Global data and analytics (GDA), responsible for developing and delivering advanced simulation models, optimizations and AI/ML models for container shipping
 
 
 terminals. As an AI/ML Scientist, you will have a leading role in designing, building, maintaining, and
 
 
 iterating on products that directly impact terminal operations.
 
 
 This position offers a unique opportunity to develop and apply your deep knowledge of simulation, optimization, data science methods, software engineering, and modern AI development tools to create
 
 
 operational and strategic insights that are transforming container terminal operations globally.
 
 
 This is an exciting time to join a growing and dynamic team that solves some of the toughest problems in
 
 
 terminal operations and builds the future of container shipping. We offer a unique opportunity to impact global trade via world-leading container terminals. We focus on our people and the right candidate will have broad
 
 
 possibilities to further develop competencies in an environment characterized by change and continuous Progress.
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Design, implement and deliver advanced simulation models and optimization solutions for terminal operations including container handling equipment efficiency, yard positioning strategies, vessel loading/unloading sequencing, and truck routing.
 </li>
 <li>
 Develop and maintain efficient applied engineering solutions that solve real-world operational challenges at container terminals globally.
 </li>
 <li>
 Build both operational tools for day-to-day terminal operations and strategic models for long-term planning and decision-making.
 </li>
 <li>
 Work with relevant stakeholders to understand terminal operational dynamics and business processes, incorporating their needs into products to enhance value delivery.
 </li>
 <li>
 Collaborate and communicate model rationale, results and insights with product teams, leadership and business stakeholders to roll out solutions to production environments.
 </li>
 <li>
 Analyse data, measure delivered value, and continuously evaluate and improve models to increase effectiveness and operational impact.
 
 
 </li>
 </ul>
 To do this job, we imagine you have:
 
 
 <ul>
 <li>
 5+ years of industry experience in building and delivering simulation models, optimization solutions, or data science products.
 </li>
 <li>
 PhD or M.Sc. in Operations Research, Industrial Engineering, Machine Learning, Statistics, Applied Mathematics, Computer Science, or other field related to algorithms and data (or equivalent experience).
 </li>
 <li>
 Strong experience in simulation modeling and optimization, particularly in operational environments with complex dynamics.
 </li>
 <li>
 Research or industry experience in one or more: Discrete event simulation, Combinatorial optimization problems (e.g., scheduling, vehicle routing, bin packing, sequencing), Continuous optimization problems (e.g., linear programming, mixed-integer programming, convex programming), AI/ML methods for operational problems, Prescriptive analytics (e.g., stochastic optimization, reinforcement learning).
 </li>
 <li>
 Experience with AI development tools and code assistants (GitHub Copilot, Cursor, Claude Code, or similar) for enhanced productivity.
 </li>
 <li>
 Excellent record of delivery using Python and technologies like Git, JIRA, etc.
 </li>
 <li>
 Ability to understand complex operational systems and translate business requirements into effective technical solutions.
 </li>
 <li>
 Strong communication skills with ability to work independently with stakeholders while liaising and reviewing with the team.
 </li>
 <li>
 Experience working with cloud environments.
 
 
 </li>
 </ul>
 Nice to have:
 
 
 <ul>
 <li>
 Experience in container terminal operations, port logistics, or similar operational environments with complex resource allocation and scheduling dynamics.
 </li>
 <li>
 Familiarity with container handling equipment, yard operations, or vessel operationsExperience in material handling, manufacturing operations, or other domains involving physical asset optimization and sequencing problems.
 </li>
 <li>
 Experience developing and interacting with generative AI models.
 
 
 </li>
 </ul>
 Maersk is committed to a diverse and inclusive workplace, and we embrace different styles of thinking. Maersk is an equal opportunities employer and welcomes applicants without regard to race, colour, gender, sex, age, religion, creed, national origin, ancestry, citizenship, marital status, sexual orientation, physical or mental disability, medical condition, pregnancy or parental leave, veteran status, gender identity, genetic information, or any other characteristic protected by applicable law. We will consider qualified applicants with criminal histories in a manner consistent with all legal requirements.
 
 
 We are happy to support your need for any adjustments during the application and hiring process. If you need special assistance or an accommodation to use our website, apply for a position, or to perform a job, please contact us by emailing accommodationrequests@maersk.com.
</div>

AI/ML Scientist(Operations research/Optimization/Simulation)

eBay

<div>At eBay, we're more than a global ecommerce leader &mdash; we&rsquo;re changing the way the world shops and sells. Our platform empowers millions of buyers and sellers in more than 190 markets around the world. We&rsquo;re committed to pushing boundaries and leaving our mark as we reinvent the future of ecommerce for enthusiasts.
Our customers are our compass, authenticity thrives, bold ideas are welcome, and everyone can bring their unique selves to work &mdash; every day. We're in this together, sustaining the future of our customers, our company, and our planet.
Join a team of passionate thinkers, innovators, and dreamers &mdash; and help us connect people and build communities to create economic opportunity for all.
At eBay, payments are at the heart of every transaction. As an ML Data Scientist on our Payments Engineering team, you&rsquo;ll help design and build the ML systems that secure and optimize financial transactions for millions of users worldwide. This is a unique opportunity to apply state-of-the-art machine learning from deep learning to generative AI models in a large-scale, high-traffic e-commerce environment. You&rsquo;ll work closely with other engineers, data scientists, and product leaders to create real-time, intelligent systems that make buying and selling on eBay safer and more seamless. This role emphasizes designing new algorithms, publishing innovative work, and pushing the boundaries of AI research while applying these breakthroughs to real-world problems.
What you will accomplish:<ul><li>
Build , Train and deploy ML models for intelligent payment routing, personalization, and intelligent decisioning in payments.</li><li>
Perform feature engineering, data preprocessing, and large-scale data analysis.</li><li>
Research, design, and implement novel machine learning and AI algorithms across areas such as deep learning, generative models, reinforcement learning, NLP, or computer vision.</li><li>
Design, train, and optimize machine learning models for a variety of business applications (classification, regression, recommendation, and personalization).</li><li>
Construct robust ML pipelines for training, validation, and deployment using modern ML stacks.</li><li>
Apply prompt engineering techniques with Generative AI models (LLMs, diffusion models, etc.) to tackle application-driven problems.</li><li>
Leverage vector databases and build/optimize embeddings for search, retrieval, and semantic understanding.</li><li>
Conduct large-scale experiments, develop benchmarks, and evaluate new approaches against existing solutions.</li><li>
Stay at the forefront of ML research, proactively identifying emerging techniques that can create business and product advantages.</li><li>
Knowledge Sharing: Contribute to internal technical discussions, mentoring, and sharing research insights with engineering teams.</li><li>
Prototype new approaches and publish in leading ML conferences/journals when applicable.</li><li>
Collaborate with engineers and product teams to build robust ML-powered applications.</li></ul> 
What You Will Bring:<ul><li>
4 + Years of applied research experience in machine learning or AI
</li><li>Proficiency in Python and ML libraries/frameworks (e.g., PyTorch, TensorFlow, JAX).</li><li>
Strong mathematical and algorithmic background (optimization, probability, statistics, linear algebra).</li><li>
Solid foundation in statistics, predictive modeling, and information retrieval.</li><li>
Experience with large-scale experimentation, distributed training, and working with big data systems.</li><li>
Familiarity with real-world applications such as LLM, NLP, computer vision, or recommendation systems.</li><li>
Knowledge of statistical techniques including regression, time series analysis, hypothesis testing, combining disparate data sources.</li><li>
Expertise with applying predictive modeling techniques, statistics and information retrieval methods to real-world data</li><li>
Hands on experience with SQL/Hive/Spark, data mining and big data query optimization</li><li>
Extensive experience with large data sets and data manipulation.</li><li>
Excellent problem-solving skills and experience in deploying predictive models in production environments.</li></ul>
 Education: MS or Bachelor&rsquo;s in Computer Science, Machine Learning, Statistics, or related field
Please see the Talent Privacy Notice for information regarding how eBay handles your personal data collected when you use the eBay Careers website or apply for a job with eBay.
eBay is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, gender identity, veteran status, and disability, or other legally protected status. If you have a need that requires accommodation, please contact us at talent@ebay.com. We will make every effort to respond to your request for accommodation as soon as possible. View our accessibility statement to learn more about eBay's commitment to ensuring digital accessibility for people with disabilities. 
The eBay Jobs website uses cookies to enhance your experience. By continuing to browse the site, you agree to our use of cookies. Visit our Privacy Center for more information.</div>

ML Data Scientist, Payments

Glance

<div>
 
 
 What you will be doing
 
 
 
 We are looking for a Data Scientist who can operate at the intersection of
 
 classical machine learning
 
 ,
 
 large-scale recommendation systems
 
 , and
 
 modern agentic AI systems
 
 .
 
 
 You will design, build, and deploy intelligent systems that power Glance&rsquo;s personalized lock screen and live entertainment experiences. This role blends deep ML craftsmanship with forward-looking innovation in autonomous/agentic systems.
 
 
 
 Your responsibilities will include:
 
 
 
 
 Classical ML &amp; Recommendation Systems
 
 
 <ul>
 <li>
 Design and develop large-scale recommendation systems using advanced ML, statistical modelling, ranking algorithms, and deep learning.
 </li>
 <li>
 Build and operate machine learning models on diverse, high-volume data sources for personalization, prediction, and content understanding.
 </li>
 <li>
 Develop rapid experimentation workflows to validate hypotheses and measure real-world business impact.
 </li>
 <li>
 Own data preparation, model training, evaluation, and deployment pipelines in collaboration with engineering counterparts.
 </li>
 <li>
 Monitor ML model performance using statistical techniques; identify drifts, failure modes, and improvement opportunities.
 </li>
 </ul>
 
 
 Agentic Systems &amp; Next-Gen AI
 
 
 <ul>
 <li>
 Build and experiment with
 
 agentic AI systems
 
 that autonomously observe model performance, trigger experiments, tune hyperparameters, improve ranking policies, or orchestrate ML workflows with minimal human intervention.
 </li>
 <li>
 Apply
 
 LLMs, embeddings, retrieval-augmented architectures, and multimodal generative models
 
 for semantic understanding, content classification, and user preference modelling.
 </li>
 <li>
 Design intelligent agents that can automate repetitive decision-making tasks&mdash;e.g., candidate generation tuning, feature selection, or context-aware content curation.
 </li>
 <li>
 Explore reinforcement learning, contextual bandits, and self-improving systems to power next-generation personalization.
 </li>
 </ul>
 
 
 Cross-functional impact
 
 
 <ul>
 <li>
 Collaborate with Designers, UX Researchers, Product Managers, and Software Engineers to integrate ML and GenAI-driven features into Glance&rsquo;s consumer experiences.
 </li>
 <li>
 Contribute to Glance&rsquo;s ML/AI thought leadership&mdash;blogs, case studies, internal tech talks, and industry conferences.
 </li>
 <li>
 Thrive in a multi-functional, highly collaborative team environment with engineering, product, business, and creative teams.
 </li>
 <li>
 Plus: Interface with stakeholders across Product, Business, Data, and Infrastructure to align ML initiatives with strategic priorities.
 </li>
 </ul>
 
 
 
 
 We are seeking candidates with deep expertise in ML, recommendation systems, and a strong appetite for building agentic AI systems.
 
 
 You should have experience with:
 
 <ul>
 <li>
 Large-scale ML and recommendation systems (collaborative filtering, ranking models, content-based approaches, embeddings).
 </li>
 <li>
 Classical ML and deep learning techniques across NLP, sequence modelling, RL, clustering, and time series.
 </li>
 <li>
 Experience in deploying ML workflows/models in production system
 </li>
 <li>
 Big data processing (Spark, distributed data systems) and cloud computing.
 </li>
 <li>
 Designing end-to-end ML solutions&mdash;from prototype to production.
 </li>
 <li>
 Plus: Building or experimenting with LLMs, generative models, and agentic AI workflows (e.g., autonomous evaluators, self-improving pipelines, automated experiment agents).
 </li>
 </ul>
 
 
 
 
 
 Qualifications
 
 
 <ul>
 <li>
 Bachelor&rsquo;s/master&rsquo;s in computer science, Statistics, Mathematics, Electrical Engineering, Operations Research, Economics, Analytics, or related fields. PhD is a plus.
 </li>
 <li>
 6+ years of industry experience in ML/Data Science, ideally in large-scale recommendation systems or personalization.
 </li>
 <li>
 Experience with LLMs, retrieval systems, generative models, or agentic/autonomous ML systems is highly desirable.
 </li>
 <li>
 Expertise with algorithms in NLP, Reinforcement Learning, Time Series, and Deep Learning, applied on real-world datasets.
 </li>
 <li>
 Proficient in Python and comfortable with statistical tools (R, NumPy, SciPy, PyTorch/TensorFlow, etc.).
 </li>
 <li>
 Strong experience with the big data ecosystem (Spark, Hadoop) and cloud platforms (Azure, AWS, GCP/Vertex AI).
 </li>
 <li>
 Comfortable working in cross-functional teams.
 </li>
 <li>
 Familiarity with privacy-preserving ML and identity-less ecosystems (especially on iOS and Android).
 </li>
 <li>
 Excellent communication skills with the ability to simplify complex technical concepts.
 </li>
 </ul>
 
 
 
 We value curiosity, problem-solving ability, and a strong bias toward experimentation and production impact.
 
 
 Our team includes engineers, physicists, economists, mathematicians, and social scientists&mdash;a great data scientist can come from anywhere.
 
</div>

Machine Learning Engineer III - Recommendation Systems

Swiggy

<div>Job Profile: Data Scientist II
Location: Bangalore | Karnataka
Years of Experience: 2 - 5 
Data Science at Swiggy
Data Science and applied ML is ingrained deeply in decision making and product development at Swiggy. Our data scientists work closely with cross-functional teams to ship end-to-end data products, from formulating the business problem in mathematical/ML terms to iterating on ML/DL methods to taking them to production. We own or co-own several initiatives with a direct line of sight to impact on customer experience as well as business metrics. We also encourage open sharing of ideas and publishing in internal and external avenues 
What will you get to do here?<ul><li>
You will leverage your strong ML/DL/Statistics background to build new and next generation of ML based solutions to improve the quality of ads recommendation and leverage various optimization techniques to improve the campaign performance.</li><li>
You will mine and extract relevant information from Swiggy's massive historical data to help ideate and identify solutions to business and CX problems.</li><li>
You will work closely with engineers/PMs/analysts on detailed requirements, technical designs, and implementation of end-to-end inference solutions at Swiggy scale.</li><li>
You will stay abreast with the latest in ML research for Ads Bidding algorithms, Recommendation Systems related areas and help adapt it to Swiggy's problem statements.</li><li>
You will publish and talk about your work in internal and external forums to both technical and layman audiences.</li><li>
Opportunity to work on challenging and impactful projects in the logistics domain</li><li>
Collaborate with cross-functional teams, including software developers and product managers, to integrate data-driven solutions into our systems</li><li>
Develop and deploy machine learning and deep learning models</li><li>
Take ownership of projects from inception to delivery, ensuring high-quality and impactful results.</li></ul> 
What qualities are we looking for?<ul><li>
Masters degree in areas related to Applied Mathematics, Machine Learning, Statistics, Operations Research</li><li>
with 2 to 6 years of industry/research lab experience</li><li>
Technically hands-on with deep dive expertise in applying ML to big data</li><li>
History of having shipped ML data products</li><li>
 Results-oriented team player with a strong sense of ownership</li><li>
 Experience working with software developers, product managers and overall SDLC</li><li>
 Experience in Deep Learning and previous experience in startups and/or product-based consumer/internet</li><li>
companies is preferred</li></ul> 
Visit our tech blogs to learn more about some the challenges we deal with:
https://bytes.swiggy.com/the-swiggy-delivery-challenge-part-one-6a2abb4f82f6
https://bytes.swiggy.com/how-ai-at-swiggy-is-transforming-convenience-eae0a32055ae
https://bytes.swiggy.com/decoding-food-intelligence-at-swiggy-5011e21dbc86 
We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, disability status, or any other characteristic protected by the law.</div>

Data Scientist II View Jobs

Weekday AI (YC W21)

<div>
 
 This role is for one of the Weekday's clients
 
 
 
 
 Salary range: Rs 1000000 - Rs 2000000 (ie INR 10-20 LPA)
 
 
 
 Min Experience: 4 years
 
 
 Location: Bangalore
 
 
 JobType: full-time
 
 
 We are looking for a Data Scientist to lead the end-to-end data science lifecycle&mdash;from problem definition and hypothesis development to model deployment planning and performance evaluation. This role focuses on building scalable, production-ready machine learning solutions that drive insights across content, audience, growth, and revenue use cases.
 
 
 You will work closely with product, editorial, growth, sales, and engineering teams to identify high-impact opportunities and translate complex data into actionable business outcomes.
 
 
 
 Requirements
 
 
 
 
 
 Key Responsibilities
 
 
 
 
 <ul>
 <li>
 Own the complete data science workflow including problem framing, feature engineering, model development, validation, and deployment planning
 </li>
 <li>
 Develop and operationalize machine learning models for forecasting, personalization, churn prediction, attribution, ranking, and content intelligence
 </li>
 <li>
 Build content and audience intelligence using NLP techniques such as embeddings, semantic similarity, topic and entity modeling, summarization, and relevance scoring
 </li>
 <li>
 Design sales and advertising analytics solutions including demand forecasting, pricing optimization, uplift modeling, and campaign effectiveness measurement
 </li>
 <li>
 Perform advanced statistical analysis including causal inference, A/B testing, experiment design, incrementality, and uplift measurement
 </li>
 <li>
 Partner with data engineering teams to develop scalable data pipelines and model training workflows
 </li>
 <li>
 Define and maintain unified KPIs and measurement frameworks to evaluate content performance and audience behavior across platforms
 </li>
 <li>
 Monitor model performance, detect drift, ensure robustness, fairness, and governance of deployed models
 </li>
 <li>
 Deliver executive-ready insights through dashboards, automated reports, and clear data storytelling
 </li>
 <li>
 Collaborate with cross-functional teams to prioritize initiatives with the highest business impact
 </li>
 <li>
 Contribute to code and design reviews, mentor peers, and raise analytical standards across the organization
 
 
 </li>
 </ul>
 
 Required Skills &amp; Experience
 
 
 
 
 
 Must-Have
 
 
 
 
 <ul>
 <li>
 4-7 years of applied data science experience delivering measurable business impact
 </li>
 <li>
 Strong proficiency in Python (pandas, NumPy, scikit-learn, statsmodels) and SQL
 </li>
 <li>
 Hands-on experience building and validating ML models including regression, classification, forecasting, clustering, recommendation systems, uplift models, and NLP-based solutions
 </li>
 <li>
 Solid foundation in statistics, probability, hypothesis testing, experimental design, and causal inference
 </li>
 <li>
 Experience working with large-scale datasets and cloud platforms such as AWS, Azure, or GCP
 </li>
 <li>
 Familiarity with BI and visualization tools like Tableau, Power BI, or Plotly
 </li>
 <li>
 Strong analytical thinking, communication, and data storytelling skills
 
 
 </li>
 </ul>
 
 
 Good-to-Have
 
 
 
 
 <ul>
 <li>
 Experience with deep learning frameworks such as TensorFlow or PyTorch
 </li>
 <li>
 Exposure to big data technologies like Spark, Hadoop, or Databricks
 </li>
 <li>
 Familiarity with MLOps practices, model monitoring, and production ML workflows
 
 
 </li>
 </ul>
 
 
 Education
 
 
 
 
 <ul>
 <li>
 Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field
 
 
 </li>
 </ul>
 
 Key Skills
 
 
 
 Data Science
 
 
 <ul>
 <li>
 Python
 </li>
 <li>
 Pandas
 </li>
 <li>
 NLP
 </li>
 <li>
 Machine Learning
 </li>
 <li>
 SQL
 </li>
 <li>
 AWS
 </li>
 <li>
 Statistics
 </li>
 <li>
 Experimentation
 </li>
 </ul>
</div>

Data Scientist

Talentxo

Data Scientist (Product Company) &ndash; MumbaiWe are hiring a Data Scientist for a consumer internet product company in Mumbai. This role focuses on building, deploying, and scaling ML models that directly impact product performance and user outcomes.Required Experience: 2&ndash;5 yearsYou must have:<ul><li>2+ years hands-on experience as a Data Scientist or ML Engineer building ML models end-to-end</li><li>Strong Python with ability to implement classical ML algorithms (regression, trees, boosting, etc.)</li><li>Experience in minimum 2+ use cases among recommendation systems, image data, fraud/risk detection, price modelling, propensity models</li><li>Strong NLP exposure (text gen/classification, embeddings, similarity, user profiling, feature extraction from unstructured text)</li><li>Practical experience productionizing models using APIs / CI/CD / Docker on AWS or GCP</li><li>Product company experience only (not financial domains)</li></ul>What you will work on: Recommendation &amp; ranking, personalization, fraud/risk, pricing models, churn/propensity, A/B test design, monitoring model &amp; data drift.Location: Mumbai, Maharashtra Working Days: 5 days/week Outstation Candidates: Allowed if willing to relocate Max Notice Period: 30 daysJob Type: Full-timePay: ₹2,100,000.00 - ₹2,800,000.00 per yearExperience:<ul><li>Data Scientist or ML Engineer: 2 years (Required)</li></ul>Work Location: In person

Wayfair

<div><div>Who we are:

Wayfair is an online retail platform with the mission to enable everyone to live in a home they love. To do this Wayfair builds and leverages cutting edge Machine Learning and AI products and we are looking for talented individuals to join us. Wayfair&rsquo;s Search, Marketing, and Recommendations ML teams build algorithmic systems that drive our business, enhance customer experience, and improve customer loyalty powering what our customers see on and off our site at web scale. You will be part of a cross-functional, collaborative team driving development of world-class ML systems that drive real-world impact.

We are looking for machine-learning scientists for research and development of the ML systems that power our real-time Search type-ahead, content recommendations, and algorithmic customer understanding experience. In this role, you&rsquo;ll partner with fellow scientists, engineers, analysts, and product managers to apply science and machine learning skills to directly impact Wayfair&rsquo;s revenue.

What you&rsquo;ll do
<ul>
<li>Design, build, deploy and refine large-scale machine learning models and algorithmic decision-making systems that solve real-world problems for customers</li>
<li>
Work cross-functionally with commercial stakeholders to understand business problems or opportunities and develop appropriately scoped analytical solutions</li>
<li>
Collaborate closely with various engineering, infrastructure, and ML platform teams to ensure adoption of best-practices in how we build and deploy scalable ML services</li>
<li>
Identify new opportunities and insights from the data (where can the models be improved? what is the projected ROI of a proposed modification?)</li>
<li>
Be obsessed with the customer and maintain a customer-centric lens in how we frame, approach, and ultimately solve every problem we work on.</li>
</ul>
We Are a Match Because You Have:
<ul>
<li>Bachelor's or Master&rsquo;s degree in Computer Science, Mathematics, Statistics, or related field.</li>
<li>
6-9 years of industry experience in developing machine learning algorithms</li>
<li>
Proficiency in Python or one other high-level programming language</li>
<li>
Solid hands-on expertise deploying machine learning solutions into production</li>
<li>
Strong theoretical understanding of statistical models such as regression, clustering and ML algorithms such as decision trees, neural networks, etc.</li>
<li>
Strong written and verbal communication skills, ability to synthesize conclusions for non-experts, and overall bias towards simplicity</li>
<li>
Intellectual curiosity and enthusiastic about continuous learning</li>
</ul>
Nice to have
<ul>
<li>Experience with Python ML ecosystem (numpy, pandas, sklearn, XGBoost, etc.) and/or Apache Spark Ecosystem (Spark SQL, MLlib/Spark ML)</li>
<li>
Familiarity with GCP (or AWS, Azure), ML model development frameworks, ML orchestration tools (Airflow, Kubeflow or MLFlow)</li>
<li>
Experience in information retrieval, query/intent understanding, search ranking, recommender systems etc.</li>
<li>
Experience with deep learning frameworks like PyTorch, Tensorflow, etc.</li>
</ul>
</div><div>Assistance for Individuals with Disabilities 
Wayfair is fully committed to providing equal opportunities for all individuals, including individuals with disabilities. As part of this commitment, Wayfair will make reasonable accommodations to the known physical or mental limitations of qualified individuals with disabilities, unless doing so would impose an undue hardship on business operations. If you require a reasonable accommodation to participate in the job application or interview process, please let us know by completing our Accomodations for Applicants form. 
 
Need Technical Assistance? 
For more information about applying for a career at wayfair, visit our FAQ page here. 
 
About Wayfair Inc. 
Wayfair is one of the world&rsquo;s largest online destinations for the home. Whether you work in our global headquarters in Boston, or in our warehouses or offices throughout the world, we&rsquo;re reinventing the way people shop for their homes. Through our commitment to industry-leading technology and creative problem-solving, we are confident that Wayfair will be home to the most rewarding work of your career. If you&rsquo;re looking for rapid growth, constant learning, and dynamic challenges, then you&rsquo;ll find that amazing career opportunities are knocking.

No matter who you are, Wayfair is a place you can call home. We&rsquo;re a community of innovators, risk-takers, and trailblazers who celebrate our differences, and know that our unique perspectives make us stronger, smarter, and well-positioned for success. We value and rely on the collective voices of our employees, customers, community, and suppliers to help guide us as we build a better Wayfair &ndash; and world &ndash; for all. Every voice, every perspective matters. That&rsquo;s why we&rsquo;re proud to be an equal opportunity employer. We do not discriminate on the basis of race, color, ethnicity, ancestry, religion, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, genetic information, or any other legally protected characteristic.

Your personal data is processed in accordance with our Candidate Privacy Notice (https://www.wayfair.com/careers/privacy). If you have any questions or wish to exercise your rights under applicable privacy and data protection laws, please contact us at dataprotectionofficer@wayfair.com.</div></div>

Machine Learning Scientist III, Customer Technology

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Machine Learning Scientist III, Customer Technology