applied scientist india machine learning

Amazon

<div>
 
 Description
 
 
 
 Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon&rsquo;s customers? Do you want to build and deploy advanced algorithmic systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning and team for India Consumer Businesses.
 
 
 If you have an entrepreneurial spirit, know how to deliver, love to work with data, are deeply technical, highly innovative and long for the opportunity to build solutions to challenging problems that directly impact the company's bottom-line, we want to talk to you.
 
 
 Major responsibilities
 
 
 <ul>
 <li>
 Use machine learning and analytical techniques to create scalable solutions for business problems
 </li>
 <li>
 Analyze and extract relevant information from large amounts of Amazon&rsquo;s historical business data to help automate and optimize key processes
 </li>
 <li>
 Design, development, evaluate and deploy innovative and highly scalable models for predictive learning
 </li>
 <li>
 Research and implement novel machine learning and statistical approaches
 </li>
 <li>
 Work closely with software engineering teams to drive real-time model implementations and new feature creations
 </li>
 <li>
 Work closely with business owners and operations staff to optimize various business operations
 </li>
 <li>
 Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation
 </li>
 <li>
 Mentor other scientists and engineers in the use of ML techniques
 
 
 </li>
 </ul>
 
 About The Team
 
 
 
 The India Machine Learning team works closely with the business and engineering teams in building ML solutions that create an impact for Amazon's IN businesses. This is a great opportunity to leverage your machine learning and data mining skills to create a direct impact on consumers and end users.
 
 
 
 Basic Qualifications
 
 
 
 <ul>
 <li>
 Master's degree or above in computer science, computer engineering, or related field
 </li>
 <li>
 Experience programming in Java, C++, Python or related language
 </li>
 <li>
 3+ years of building models for business application experience
 </li>
 <li>
 PhD, or a Master's degree and experience building machine learning models or developing algorithms for business application
 </li>
 <li>
 Experience in patents or publications at top-tier peer-reviewed conferences or journals
 </li>
 <li>
 Experience programming in Java, C++, Python or related language
 </li>
 <li>
 Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience implementing algorithms using both toolkits and self-developed code
 </li>
 <li>
 Have publications at top-tier peer-reviewed conferences or journals
 
 
 </li>
 </ul>
 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.
 
 
 
 
 Company
 
 - ADCI - Karnataka
 
 
 Job ID: A3089323
</div>

Applied Scientist, India Machine Learning

Microsoft

<div>
 
 Overview
 
 
 
 We are seeking a passionate and technically skilled Data Scientist II to join the Commerce &ndash; Platforms, Data, and Experiences (PDX) team. This team plays a pivotal role in shaping Microsoft&rsquo;s commerce data strategy, building scalable data platforms, and delivering actionable ML driven insights that drive business transformation across the ecosystem.
 
 
 As a Data Scientist II in PDX, you will work at the intersection of data engineering, data processing, and machine learning to solve complex business problems. You will collaborate with cross-functional teams to design experiments, build predictive models, and develop scalable solutions that enhance decision-making and customer experiences by producing descriptive, diagnostic, predictive and prescriptive insights.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Design and implement advanced analytics solutions to support commerce data platform initiatives including analytics based on Machine Learning Models.
 </li>
 <li>
 Partner with engineering and product teams to define data requirements and ensure high-quality data pipelines.
 </li>
 <li>
 Conduct exploratory data analysis, feature engineering, and model evaluation using structured and unstructured datasets.
 </li>
 <li>
 Ensure the models built are operable, scalable, extensible and performant.
 </li>
 <li>
 Develop dashboards, visualizations, and storytelling artifacts to communicate insights to stakeholders.
 </li>
 <li>
 Lead experimentation efforts to evaluate new features, forecasting, data quality and anomaly detection systems.
 </li>
 <li>
 Build extensible solutions on LLM models to improve productivity of engineers across the commerce organization.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Statistics, Mathematics, or related field.
 </li>
 <li>
 2+ years of experience in data science, analytics, or applied machine learning.
 </li>
 <li>
 Proficiency in Python, SQL, and ML frameworks (e.g., Scikit-learn, TensorFlow, PyTorch).
 </li>
 <li>
 Experience with cloud platforms (Azure preferred) and big data technologies.
 </li>
 <li>
 Strong understanding of statistical modeling, predictive analytics, and experimentation design.
 </li>
 <li>
 Excellent communication and stakeholder management skills.
 </li>
 <li>
 Demonstrated experience leveraging AI tools and technologies to enhance engineering effectiveness, coupled with a strong curiosity and commitment to continuous learning in the field of Artificial Intelligence.
 
 
 </li>
 </ul>
 This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
 
 
 Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about
 
 requesting accommodations.
 
</div>

Data Scientist II

<div>
 
 Overview
 
 
 
 The Data and Artificial Intelligence team in Microsoft&rsquo;s Developer Division, part of newly formed CoreAI group, is working on the future of AI for Developers! We are a diverse, entrepreneurial and multi-disciplinary group of scientists, researchers and engineers with passion for using AI to improve the productivity of millions of developers around the world. We have released AI for code advancements in Github Copilot, VS Code, Visual Studio and other Microsoft Copilots.
 
 
 We are looking for a passionate and growth-oriented Senior Applied Scientist to join our team working on high-impact projects at the intersection of AI and software engineering. As an Applied Scientist, you will play a pivotal role in development and application of advanced data science techniques&mdash;especially those involving LLMs&mdash;to real-world developer workflows. You&rsquo;ll collaborate closely with data scientists, engineers, researchers, and product teams across Microsoft and GitHub to shape the next generation of AI-powered developer workflows. You will have the opportunity to design and lead experiments, build and evaluate state-of-the-art models (including RAG pipelines, finetuning and evaluation frameworks), turning insights into scalable product features. Most importantly, you&rsquo;ll play a key role in bridging cutting-edge research and production, using data to inform decisions, drive iteration, and deliver measurable impact at scale.
 
 
 Microsoft&rsquo;s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Research and productization of state-of-the-art in AI for Software Engineering.
 </li>
 <li>
 Build and manage large-scale AI experiments and models.
 </li>
 <li>
 Drive experimentation through A/B testing and offline validation to evaluate model performance.
 </li>
 <li>
 Collaborate across disciplines and geographies with product teams in Microsoft and Github, integrate AI across software development stack for Copilot.
 </li>
 <li>
 Stay up to date with the research literature and product advances in AI for software engineering
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 Required Minimum Qualifications:
 
 
 <ul>
 <li>
 Undergraduate degree in Computer Science, Engineering, Mathematics, Statistics.
 </li>
 <li>
 6+ years experience with strong proficiency in Python, machine learning frameworks, and experience developing and deploying generative AI or machine learning models into production. (Experience with additional programming languages is a plus but not required.)
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Masters or PhD degree in Computer Science, Statistics, or related fields (undergraduates with significant appropriate experience will be considered).
 </li>
 <li>
 Strong professional experience in statistics, machine learning, including deep learning, NLP, econometrics.
 </li>
 <li>
 Experience in building cloud-scale systems and experience working with open-source stacks for data processing and data science is desirable.
 </li>
 <li>
 Experience with LLMs in natural language, AI for code or related fields
 </li>
 <li>
 Excellent communication skills, ability to present and write reports, strong teamwork and collaboration skills.
 </li>
 <li>
 Experience in productizing AI and collaborating with multidisciplinary teams.
 
 
 </li>
 </ul>
 This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
 
 
 Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about
 
 requesting accommodations.
 
</div>

Senior Data Scientist

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

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

Qualitest

<div>
 
 Data Scientist &ndash; QA &amp; AI Enablement (Hub Model)
 
 
 Role Summary
 
 
 
 We are seeking one Data Scientist to join the Hub component of the client hub-and-spoke engagement model. The Data Scientist will play a key role in supporting the deployment, refinement, and optimization of Coco bots and AI-driven quality engineering initiatives.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Participate in daily stand-up meetings, provide status updates, highlight risks, and deliver daily and weekly status reports.
 </li>
 <li>
 Collaborate with business and technical stakeholders to gather representative and high-quality datasets for AI model development and testing.
 </li>
 <li>
 Perform statistical analysis, data visualization, data cleansing, and preparation of datasets for AI/ML testing and validation.
 </li>
 <li>
 Evaluate the effectiveness, reliability, and accuracy of new and existing data sources using appropriate data assessment techniques.
 </li>
 <li>
 Apply predictive modeling techniques to improve QA efficiency and optimize broader business outcomes.
 </li>
 <li>
 Coordinate with cross-functional teams to implement data models and monitor their operational outcomes.
 </li>
 <li>
 Develop and maintain processes, metrics, and tools to continuously monitor model performance, data quality, and accuracy over time.
 
 
 </li>
 </ul>
 
 Required Skills &amp; Experience (Must Haves)
 
 
 
 <ul>
 <li>
 AI / Machine Learning: Proficiency level 4/5
 </li>
 <li>
 Predictive Modeling: Proficiency level 4/5
 </li>
 <li>
 Data Modeling Implementation: Proficiency level 3/5
 </li>
 </ul>
</div>

Data Scientist- QA and AI Enablement

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)

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