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ai/ml scientist(operations research/optimization/simulation) Jobs in Mangaluru

ai/ml scientist(operations research/optimization/simulation)

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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)

GreyOrange

<div>
 
 As an Operations Research Scientist at GreyOrange, you will play a pivotal role in designing, developing, and implementing advanced models and algorithms that enhance decision-making across various business functions.
 
 
 You will collaborate with cross-functional teams, including product development, engineering, to optimize processes, improve product performance, and solve complex problems using mathematical and computational methods.
 
 
 The ideal candidate has a deep understanding of optimization, statistical modeling, and machine learning, with a passion for solving real-world problems in a high-tech environment.
 
 
 
 Roles and responsibilities:
 
 
 <ul>
 <li>
 Develop and apply advanced operations research models, including optimization, simulation, and stochastic models, to solve complex business challenges.
 </li>
 <li>
 Work closely with engineering, data science, and product teams to integrate OR models into SaaS platforms, providing actionable insights to enhance product performance.
 </li>
 <li>
 Design and implement optimization algorithms (e.g., linear programming, mixed-integer programming, and nonlinear optimization) to drive business efficiency and effectiveness.
 </li>
 <li>
 Analyze large datasets and develop predictive models using statistical and machine learning techniques to improve decision-making processes.
 </li>
 <li>
 Develop mathematical models, simulations, or optimization algorithms to represent real-world systems or problems.
 </li>
 <li>
 Use techniques like linear programming, dynamic programming, queuing theory, or game theory to create models.
 </li>
 <li>
 Build simulation models to evaluate potential solutions and improve resource allocation, scheduling, and supply chain logistics.
 </li>
 <li>
 Collaborate with stakeholders to understand business requirements and translate them into mathematical models and algorithmic solutions.
 </li>
 <li>
 Collaborate with cross-functional teams such as engineering, product, and operations to implement solutions.
 </li>
 <li>
 Communicate findings, insights, and recommendations to non-technical stakeholders through reports, presentations, or data visualizations.
 </li>
 <li>
 Communicate complex mathematical concepts and results to non-technical stakeholders in a clear and understandable manner.
 </li>
 <li>
 Monitor the performance of implemented solutions and refine models over time based on feedback and new data.
 </li>
 <li>
 Stay updated with the latest advancements in operations research, machine learning, and optimization, and apply best practices to develop innovative solutions.
 </li>
 <li>
 Document models, algorithms, and analytical processes for future reference and team knowledge sharing.
 </li>
 <li>
 Generate reports that summarize the outcomes of analyses and model performance.
 </li>
 </ul>
 
 
 Requirements/Qualifications:
 
 
 <ul>
 <li>
 Master&rsquo;s or Ph.D. in Operations Research, Applied Mathematics, Industrial Engineering, Computer Science, or a related field.
 </li>
 <li>
 Strong expertise in mathematical modeling, optimization techniques (linear programming, dynamic programming), and statistical analysis.
 </li>
 <li>
 Proficiency in programming languages such as Python, R, C++, and experience with optimization tools (Gurobi, CPLEX, MATLAB).
 </li>
 <li>
 Familiarity with data analysis, machine learning techniques, and simulation.
 </li>
 <li>
 Excellent problem-solving skills and the ability to translate complex problems into actionable insights.
 </li>
 <li>
 Strong collaboration skills and the ability to communicate complex concepts to non-technical stakeholders.
 </li>
 <li>
 Experience managing or contributing to research projects in a fast-paced environment.
 </li>
 </ul>
 
 
 About GreyOrange:
 
 
 <ul>
 <li>
 GreyOrange is a global leader in AI-driven robotic automation software and hardware, transforming distribution and fulfillment centers worldwide.
 </li>
 <li>
 Our solutions increase productivity, empower growth and scale, mitigate labor challenges, reduce risk and time to market, and create better experiences for customers and employees.
 </li>
 <li>
 Founded in 2012, GreyOrange is headquartered in Atlanta, Georgia, with offices and partners across the Americas, Europe and Asia.
 </li>
 </ul>
 
 
 Our Solutions:
 
 
 <ul>
 <li>
 The GreyMatter Multiagent Orchestration (MAO) platform provides vendor-agnostic fulfillment orchestration to continuously optimize performance in real time: the right order, with the right bot and agent, taking the right path and action.
 </li>
 <li>
 Currently operating more than 70 fulfillment sites across the globe (with deployments of 700+ robots at a single site), GreyMatter enables customers to decrease their fulfillment Cost Per Unit by 50%, reduce worker onboarding time by 90% and optimize peak season performance.
 </li>
 <li>
 In retail stores, our gStore end-to-end store execution and retail management solution supports omnichannel fulfillment, real-time replenishment, intelligent workforce tasking and more.
 </li>
 <li>
 Using real-time overhead RFID technology, the platform increases inventory accuracy up to 99%, doubles staff productivity, and enables an engaging, seamless in-store experience.
 </li>
 </ul>
 
 
 EEO:
 
 
 <ul>
 <li>
 GreyOrange 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.
 </li>
 <li>
 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.
 </li>
 </ul>
</div>

Operations Research 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

Intuit

<div>
 
 Overview
 
 
 
 Intuit is seeking a Sr AI Scientist to join our AI Science team in Intuit India for the Virtual Expert Platform (VEP) Organization.
 
 
 We&rsquo;re investing in a culture of &ldquo;builders&rdquo; by fostering an environment where innovation, creativity, and bold thinking are encouraged. I believe that the &ldquo;builder&rdquo; mindset is necessary for us to accelerate our move toward AI-native experiences. This requires more builders who can rapidly apply AI and emerging technologies to solve our customers&rsquo; problems.
 
 
 Join the Virtual Expert Platform team, the driving force behind Intuit's expert service, sales, and workforce management (and other Operations Research topics), generating billions in revenue.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Practices leadership and communication skills to influence teams and to evangelize AI science across the organization
 </li>
 <li>
 Collaborates with stakeholders to define success criteria and align ML model metrics with business goals. Works side-by-side with product managers, software engineers, and designers in designing experiments and minimum viable products
 </li>
 <li>
 Leads technical work of a scrum team: initiating and designing model solutions, driving end-to-end architecture designs of the team&rsquo;s work, and holding the team accountable for high quality code, git, design, costs and implementation standards
 </li>
 <li>
 Performs hands-on data analysis and modeling with large data sets, including discovering data sources, getting data access, cleaning up data, and making them &ldquo;model-ready&rdquo;. You need to be willing and able to do your own ETL and design/build featurization.
 </li>
 <li>
 Applies data mining, NLP, and machine learning (such as supervised/unsupervised, Causal-ML, Online Learning, Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and datasets.
 </li>
 <li>
 Runs A/B tests to draw conclusions on the impact of your team&rsquo;s work and communicates results to peers and leaders
 </li>
 <li>
 Communicates with partners to ensure successful delivery and integration of DS solutions.
 </li>
 <li>
 Proactively researches, explores, and enables new AI/ML technologies. Keeps up with the new developments in academia and industry and considers possible extensions to solve Intuit customer problems.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 MS or PhD in an appropriate technology field (Computer Science, Statistics, Applied Math, Operations Research, etc.).
 </li>
 <li>
 2+ years of experience with data science for PhD and 5+ years for Masters.
 </li>
 <li>
 Experience in modern advanced analytical tools and programming languages such as R or Python with scikit-learn.
 </li>
 <li>
 Efficient in SQL, Hive, or SparkSQL, etc.
 </li>
 <li>
 Comfortable in Linux environment
 </li>
 <li>
 Experience in data mining algorithms and statistical modeling techniques such as clustering, classification, regression, decision trees, neural nets, support vector machines, anomaly detection, recommender systems, sequential pattern discovery, and text mining.
 </li>
 <li>
 Solid communication skills: Demonstrated ability to explain complex technical issues to both technical and non-technical audiences
 
 
 </li>
 </ul>
 Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit&reg;: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.
</div>

Senior AI Scientist

Microsoft

<div>
 
 Overview
 
 
 
 Overview
 
 
 With the rapid acceleration of AI and the need to deliver trustworthy, high-performing models, Microsoft&rsquo;s Customer Experience (CXP) Data Science team is driving innovation at scale! Our mission is to advance AI capabilities through rigorous evaluations, fine-tuning, and large-scale experimentation to create intelligent, personalized experiences for customers worldwide. The CXP Data Science team is seeking passionate AI practitioners and data scientists to join agile, cross-functional teams working on cutting-edge model evaluation frameworks, optimization pipelines, and experimentation platforms that power Microsoft&rsquo;s AI ecosystem.
 
 
 We are looking for an
 
 Applied AI Scientist II
 
 to join our team! As a member of the Customer Experience Data Science organization at Microsoft, you will help us accelerate the company&rsquo;s own AI transformation. You will have the opportunity to partner directly with the engineering and product management groups responsible for managing the Dynamics 365 applications that power Microsoft&rsquo;s sales, marketing, and support platforms. You will apply advanced analytics, statistical modeling, machine learning and GenAI tools to uncover insights, drive action and deliver innovative solutions for complex business challenges.
 
 
 
 This Role Offers The Opportunity To
 
 
 
 <ul>
 <li>
 Collaborate across a diverse team of data scientists, engineers, and product managers
 </li>
 <li>
 Deepen your expertise in the evolving AI and ML landscape
 </li>
 <li>
 Drive meaningful impact for thousands of Microsoft sales, marketing and support platform users
 
 
 </li>
 </ul>
 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
 
 
 
 Responsibilities
 
 
 <ul>
 <li>
 Work with key stakeholders to understand the underlying business needs and formulate the needs into discrete, manageable problems with well-defined measurable objectives and outcomes.
 </li>
 <li>
 Transform formulated problems into implementation plans by defining success metrics, applying/creating the appropriate methods, algorithms, and tools, as well as delivering statistically valid and reliable results.
 </li>
 <li>
 Write robust, reusable, and extensible code to support analysis and modeling.
 </li>
 <li>
 Develop new ML and GenAI based models using advanced statistical, ML and LLM techniques.
 </li>
 <li>
 Lead the evaluation of various GenAI based solutions, diagnosing issues and identifying root causes to support potential fine-tuning or reinforcement learning based fixes.
 </li>
 <li>
 Use AI-powered tools in your daily work to accelerate coding, analysis, and other tasks.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 Qualifications
 
 
 
 Required/Minimum Qualifications (RQs/MQs)
 
 
 
 <ul>
 <li>
 Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research)
 </li>
 <ul>
 <li>
 OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
 </li>
 <li>
 OR equivalent experience.
 </li>
 </ul>
 <li>
 Expertise in Python , PySpark, and SQL, LLMs
 </li>
 <li>
 Exposure to ML development platforms such as Azure Machine Learning, Azure AI Foundry + Azure OpenAI
 
 </li>
 </ul>
 
 Additional Or Preferred Qualifications (PQs)
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Machine Learning, Data science, Mathematics, Statistics, Computer Science, or related field AND 5+ years related experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
 </li>
 <ul>
 <li>
 OR master&rsquo;s degree in data science, Mathematics, Statistics, Computer Science, or related field AND 4+ year(s) related experience
 </li>
 <li>
 OR Doctorate in Data Science, Mathematics, Statistics, Computer Science, or related field AND 3+ year(s) related experience
 </li>
 </ul>
 <li>
 Experience in Spark and ability to write/maintain/understand declarative Spark code and to cleanly write and maintain SQL. Knowledge of finer operational aspects of Spark such as setting optimal cluster size, executor memory, number of executors etc. and experience in Azure Synapse/Databricks (or similar).
 </li>
 <li>
 Expertise in ML development platforms such as Azure Machine Learning, Azure AI Foundry + Azure OpenAI
 </li>
 <li>
 1+ year(s) experience creating publications (e.g., patents, peer-reviewed academic papers).
 
 </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 & Applied Scientist II

Rakuten Symphony

<div>
 
 
 Job Title: Data Scientist (3 to 8 Yrs)
 
 
 
 
 Location: Bangalore, Hybrid
 
 
 
 
 Preferred Skills
 
 - Telecom experience (e.g., working with network data, customer analytics) is a plus.
 
 
 
 Please note &ndash; This role requires F2F(In-Person) Interview in Bangalore office.
 
 
 
 
 
 
 
 
 Why should you choose us?
 
 
 
 
 Rakuten Symphony is a Rakuten Group company, that provides global B2B services for the mobile telco industry and enables next-generation, cloud-based, international mobile services. Building on the technology Rakuten used to launch Japan&rsquo;s newest mobile network, we are taking our mobile offering global. To support our ambitions to provide an innovative cloud-native telco platform for our customers, Rakuten Symphony is looking to recruit and develop top talent from around the globe. We are looking for individuals to join our team across all functional areas of our business &ndash; from sales to engineering, support functions to product development. Let&rsquo;s build the future of mobile telecommunications together!
 
 
 
 
 
 
 
 What Do We Expect From You
 
 
 
 
 We are seeking a skilled and motivated Data Scientist to join our team in India. The ideal candidate will play a key role in designing, building, and deploying advanced data-driven solutions to support business decision-making and enhance mobile network performance. You&rsquo;ll collaborate with cross-functional teams to transform data into actionable insights that drive innovation across Rakuten Mobile&rsquo;s operations..
 
 
 
 
 
 
 
 Roles &amp; Responsibilities:
 
 
 
 
 
 Data Modeling &amp; Analysis
 
 
 <ul>
 <li>
 Design and develop statistical and machine learning models to solve complex business problems in telecom, including customer behavior analysis, network optimization, and fraud detection.
 </li>
 <li>
 Perform exploratory data analysis, data wrangling, and feature engineering to prepare high-quality datasets for modeling.
 </li>
 </ul>
 
 
 Model Development &amp; Deployment
 
 
 <ul>
 <li>
 Build, train, evaluate, and deploy predictive models using Python and industry-standard ML frameworks.
 </li>
 <li>
 Work with engineering teams to deploy models into production environments, ensuring scalability and performance.
 </li>
 </ul>
 
 
 Business Collaboration
 
 
 <ul>
 <li>
 Partner with business stakeholders, product managers, and engineers to understand business needs and translate them into data science solutions.
 </li>
 <li>
 Present insights and model results in a clear and concise manner to both technical and non-technical audiences.
 </li>
 </ul>
 
 
 Data Infrastructure &amp; Tooling
 
 
 <ul>
 <li>
 Utilize cloud platforms (AWS, GCP, Azure) to build scalable data pipelines and ML workflows.
 </li>
 <li>
 Leverage tools like TensorFlow, PyTorch, Scikit-learn, and Spark to handle large-scale data processing and modeling.
 </li>
 </ul>
 
 
 Continuous Improvement &amp; Research
 
 
 <ul>
 <li>
 Stay current with the latest developments in AI/ML and apply new techniques to telecom-specific challenges.
 </li>
 <li>
 Contribute to the development of best practices and guidelines for data science within the team.
 </li>
 </ul>
 
 
 
 
 
 
 Skills and Qualifications:
 
 
 
 
 
 
 
 
 Education
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Data Science, Statistics, Engineering, or a related field.
 </li>
 </ul>
 
 
 Technical Expertise
 
 
 <ul>
 <li>
 Strong foundation in statistics, machine learning, and data mining techniques.
 </li>
 <li>
 Proficiency in Python and relevant libraries (Pandas, NumPy, Scikit-learn, etc.).
 </li>
 <li>
 Experience with ML frameworks (TensorFlow, PyTorch) and data processing tools (Spark, SQL).
 </li>
 <li>
 Hands-on experience with cloud services and data pipelines (AWS, GCP, or Azure).
 </li>
 <li>
 Telecom experience (e.g., working with network data, customer analytics) is a plus.
 </li>
 </ul>
 
 
 Analytical &amp; Problem-Solving Skills
 
 
 <ul>
 <li>
 Ability to analyze large datasets, extract insights, and apply them to solve business problems.
 </li>
 <li>
 Strong critical thinking skills with attention to detail and accuracy.
 </li>
 </ul>
 
 
 Communication &amp; Collaboration
 
 
 <ul>
 <li>
 Effective communicator with the ability to explain complex concepts clearly.
 </li>
 <li>
 Comfortable working in cross-functional teams and contributing to a collaborative environment.
 </li>
 </ul>
 
 
 
 
 
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience in telecom use cases such as customer churn prediction, network performance analysis, and anomaly detection.
 </li>
 <li>
 Familiarity with containerization and deployment tools (Docker, Kubernetes).
 </li>
 <li>
 Knowledge of CI/CD practices and MLOps frameworks for model lifecycle management.
 </li>
 <li>
 Exposure to NLP, time-series forecasting, or deep learning techniques.
 </li>
 </ul>
 
 
 
 
 
 Rakuten Shugi Principles:
 
 
 <ul>
 <li>
 Our worldwide practices describe specific behaviours that make Rakuten unique and united across the world. We expect Rakuten employees to model these 5 Shugi Principles of Success.
 </li>
 <li>
 
 Always improve, always advance.
 
 Only be satisfied with complete success - Kaizen.
 </li>
 <li>
 
 Be passionately professional.
 
 Take an uncompromising approach to your work and be determined to be the best.
 </li>
 <li>
 
 Hypothesize - Practice - Validate - Shikumika.
 
 Use the Rakuten Cycle to success in unknown territory.
 </li>
 <li>
 
 Maximize Customer Satisfaction.
 
 The greatest satisfaction for workers in a service industry is to see their customers smile.
 </li>
 <li>
 
 Speed!! Speed!! Speed!!
 
 Always be conscious of time. Take charge, set clear goals, and engage your team.
 </li>
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Data Scientist

Walmart Global Tech India

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 Position Summary...
 
 
 
 Job Summary
 
 
 
 As a Staff Data Scientist, you'll have the opportunity to
 
 
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 Drive data-derived insights across a wide range of retail divisions by developing advanced statistical models, machine learning algorithms and computational algorithms based on business initiatives
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 Direct the gathering of data, assess data validity and synthesize data into large analytics datasets to support project goals
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 Lead a team of Data Scientists to solve problems in Store operations domain using advanced Machine Learning and Gen AI.
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 Utilize big data analytics and advanced data science techniques to identify trends, patterns, and discrepancies in data. Determine additional data needed to support insights
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 Build and train AI/ML models for replication for future projects
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 Deploy and maintain the data science solutions
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 Communicate recommendations to business partners and influence future plans based on insights
 
 
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 What you'll do...
 
 
 
 About The Team
 
 
 
 International Data Science team at Walmart Global Tech is focused on using the latest research in machine learning, statistics and optimization to solve business problems in assortment, pricing, sourcing, customer, supply chain, and replenishment areas for multiple countries within Walmart&rsquo;s global operations. We mine data, distill insights, extract information, build analytical models, deploy Machine Learning algorithms, and use the latest algorithms and technology to empower business decision-making. We work with engineers to build reference architectures and machine learning pipelines in a big data ecosystem to productize our solutions. Advanced analytical algorithms driven by our team will help Walmart to optimize business operations, business practices and change the way our customers shop.
 
 
 
 What You&rsquo;ll Do
 
 
 
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 Consult with business stakeholders regarding algorithm-based recommendations and be a thought-leader to develop these into business actions.
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 Guides data scientists and senior data scientists across the domain DS team to ensure on-time delivery of ML products
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 Lead multiple complex ML products and guide senior tech leads in the domain in efficiently leading their products.
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 Proactive identification of complex business problems that can be solved using advanced ML and Generative AI, finding opportunities and gaps in the current business domain
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 Evaluates proposed business cases for projects and initiatives
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 Translates business requirements into strategies, initiatives, and projects and aligns them to business strategy and objectives, and drives the execution of deliverables
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 Sets relevant deliverables based on the established success criteria and define key metrics to measure progress and effectiveness of the solution
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 Quantifies business impact and ensures regular impact measurement of all ML products in the domain.
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 Identifies and reviews model evaluation metrics based on analytical requirements
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 Ensures testing information is documented and maintained by the team
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 Play a key role to solve complex problems, pivotal to Walmart's business and drive actionable insights
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 Utilize product mindset to build, scale and deploy holistic data science products after successful prototyping
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 Demonstrate incremental solution approach with agile and flexible ability to overcome practical problems
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 Articulate and present recommendations to business partners and influence plans based on insights
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 Partner and engage with associates in other regions for delivering the best services to customers around the globe
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 Work with the customer-centric mindset to deliver high-quality business-driven analytic solutions.
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 Drive innovation in approach, method, practices, process, outcome, delivery, or any component of end-to-end problem solving
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 Proactively engages in the external community to build Walmart's brand and learn more about industry practices
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 Promote and support company policies, procedures, mission, values, and standards of ethics and integrity
 
 
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 What You&rsquo;ll Bring
 
 
 
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 Bachelor's with &gt; 10 years /Masters &gt; 8 years /Ph.D. in Comp Science/Statistics/Mathematics/Quantitative discipline with &gt; 5 years of relevant experience. Educational qualifications should be Computer Science/Statistics/Mathematics or a related area.
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 Ability to lead data science projects end to end.
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 Strong experience in machine learning, supervised and unsupervised: NLP, Classification, Data/Text Mining, Multi-modal supervised and unsupervised models, Neural Networks, Deep Learning Algorithms, Generative AI models.
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 Experience in analyzing complex problems and translating them into analytical solutions.
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 Strong experience in Computer Vision, image processing, object detection, Deep learning. Exposure to image features, edge detection, blur, sharpness, corner detection, face detection, knowledge of how image data is represented.
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 Knowledge of Deep learning, CNNs, and components of CNNs, loss functions for classification, object detection, segmentation.
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 Experience in machine learning: Classification models, regression models, NLP, Forecasting, Unsupervised models, Optimization, Recommendation models, deep-learning, Graph ML, Causal inference, Causal ML, Statistical Learning, experimentation
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 Ability to utilize data science solutions outcomes to drive predictive and prescriptive analytics.
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 Experience with big data analytics - identifying trends, patterns, and outliers in large volumes of data
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 Ability to scale and deploy data science solutions.
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 Experience in LLMs, VLMs, embedding generation from multimodal data, storage and retrieval from Vector Databases, set-up and provisioning of managed LLM gateways, development of Retrieval augmented generation based LLM agents, model selection, iterative prompt engineering and finetuning based on accuracy and user-feedback, monitoring and governance.
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 Strong Experience in Python, PySpark, OpenCV, Python, C++, Keras, tensorflow, pytorch, big data platforms like Hadoop
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 Google Cloud platform, Vertex AI, Kubeflow, model deployment, Kafka streaming, API development &amp; deployment, CI/CD, MLOPs
 
 
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 Additional Preferred Qualifications:
 
 
 
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 Published papers or given talks in leading academic and research journals
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 Published papers or given talks in Data Science Forums
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 Hold data science related patents
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 Experience with GPU/CUDA for computational efficiency
 
 
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 About Walmart Global Tech
 
 
 
 Imagine working in an environment where one line of code can make life easier for hundreds of millions of people. That&rsquo;s what we do at Walmart Global Tech. We&rsquo;re a team of software engineers, data scientists, cybersecurity expert's and service professionals within the world&rsquo;s leading retailer who make an epic impact and are at the forefront of the next retail disruption. People are why we innovate, and people power our innovations. We are people-led and tech-empowered.
 
 
 We train our team in the skillsets of the future and bring in experts like you to help us grow. We have roles for those chasing their first opportunity as well as those looking for the opportunity that will define their career. Here, you can kickstart a great career in tech, gain new skills and experience for virtually every industry, or leverage your expertise to innovate at scale, impact millions and reimagine the future of retail.
 
 
 
 
 Walmart&rsquo;s culture sets us apart, and we know being together helps us innovate, learn and grow great careers. This role is based in our Bangalore office for daily work, with the flexibility for associates to manage their personal lives.
 
 
 
 
 
 Benefits
 
 
 
 Beyond our great compensation package, you can receive incentive awards for your performance. Other great perks include a host of best-in-class benefits maternity and parental leave, PTO, health benefits, and much more.
 
 
 
 Equal Opportunity Employer
 
 
 
 Walmart, Inc. is an Equal Opportunity Employer &ndash; By Choice. We believe we are best equipped to help our associates, customers, and the communities we serve live better when we really know them. That means understanding, respecting, and valuing diversity- unique styles, experiences, identities, ideas and opinions &ndash; while being inclusive of all people.
 
 
 
 Minimum Qualifications...
 
 
 
 
 
 Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.
 
 
 
 
 Minimum Qualifications:Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years' experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 2 years' experience in an analytics related field. Option 3: 6 years' experience in an analytics or related field.
 
 
 
 Preferred Qualifications...
 
 
 
 
 
 Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.
 
 
 
 
 
 Primary Location...
 
 
 
 BLOCK- 2, PRESTIGE TECH PACIFIC PARK, SY NO. 38/1P, OUTER RING ROAD KADUBEESANAHALLI, , India R-2361300
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(IND) STAFF, DATA SCIENTIST

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