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intern - data analytics associate

machine learning data scientist (blr) Jobs in Mangaluru

machine learning data scientist (blr)

product design intern

machine learning intern

Intuit

<div>
 
 Overview
 
 
 
 We are looking for an experienced Machine Learning Engineer to join Intuit&rsquo;s AI, Research, and Futures organization to build AI/Machine Learning solutions that leverage emerging new technologies and capabilities and unlock entirely new AI-driven experiences for our customers. You will be part of a vibrant team of AI Scientists and MLEs and lead efforts to translate cutting-edge research into robust, scalable AI systems that deliver measurable customer impact.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Model Prototyping: The ML Engineer would be expected to build prototype models alongside data scientists. This may involve data exploration, high-performance data processing, and machine learning algorithm exploration. The ML engineer will be expected to come up with a rationale for model choice and come up with metrics to properly evaluate models.
 </li>
 <li>
 Model Productionalization: Works with data scientists to productionalize prototype models to the point where it can be used by customers at scale. This might involve increasing the amount of data used to train the model, automation of training and prediction, and orchestration of data for continuous prediction. The engineer would be expected to understand the details of the data being used and provide metrics to compare models.
 </li>
 <li>
 Model Enhancement: Work on existing codebases to either enhance model prediction performance or to reduce training time. In this case you will need to understand the specifics of the algorithm implementation in order to enhance it. This enhancement could be exploratory work based off a performance need or directed work based off of ideas that other data science team members propose.
 </li>
 <li>
 Machine Learning Tools: The ML Engineer would build a tool for a specific project, or multiple projects though generally these types of projects are decoupled from any one project. The goal of this type of use case would be to ease a pain point in the data science process. This may involve speeding up training, making a data processing easier, or data management tooling.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 BS, MS, or PhD degree in Computer Science or related field, or equivalent practical experience.
 </li>
 <li>
 Knowledgeable with Data Science tools and frameworks (i.e. Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark).
 </li>
 <li>
 Basic knowledge of machine learning techniques (i.e. classification, regression, and clustering).
 </li>
 <li>
 Understand machine learning principles (training, validation, etc.)
 </li>
 <li>
 Knowledge of data query and data processing tools (i.e. SQL)
 </li>
 <li>
 Computer science fundamentals: data structures, algorithms, performance complexity, and implications of computer architecture on software performance (e.g., I/O and memory tuning).
 </li>
 <li>
 Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ability to write production-ready code.
 </li>
 <li>
 Mathematics fundamentals: linear algebra, calculus, probability
 </li>
 <li>
 Interest in reading academic papers and trying to implement state-of-the-art experimental systems
 </li>
 <li>
 Experience using deep learning architectures
 </li>
 <li>
 Experience deploying highly scalable software supporting millions or more users
 </li>
 <li>
 Experience with GPU acceleration (i.e. CUDA and cuDNN)
 </li>
 <li>
 Experience with integrating applications and platforms with cloud technologies (i.e. AWS and GCP)
 </li>
 <li>
 Experience with NLP and NLU
 
 
 </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. The expected base pay range for this position is:
</div>

Software Engineer 2- Machine learning

LinkedIn

<div>
 
 Company Description
 
 
 
 LinkedIn is the worlds largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. Were also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture thats built on trust, care, inclusion, and fun where everyone can succeed.
 
 
 
 Job Description
 
 
 
 Join the LSS-AI team and help create meaningful impact by connecting sellers and buyers to mutual growth opportunities! LinkedIn Sales Solutions (LSS) is one of the fastest-growing multi-billion dollar verticals at LinkedIn, and the LSS-AI team is at the forefront of building the next generation of AI-centric Sales Navigator platform. This platform enables tens of millions of companies to connect with their future customers, driving significant economic value. As a member of the LSS-AI team, you will work on cutting-edge projects, including building Agentic and GenAI-powered search and recommendation systems, tuning and applying domain-specific LLMs, and collaborating with our partner vendors like OpenAI. You will have the opportunity to work with passionate AI engineers, as well as our brilliant cross-functional partner teams in Engineering, Product Management, and Design. Together, we are creating immense economic value for our customers using the largest global professional economic graph.
 
 
 As part of a new and fast growing team of top-notch scientists and engineers, you will experience all the excitement and dynamism of a startup along with the scale and technology of a world-class enterprise.
 
 
 At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Develop advanced embedding models (text, graph, structured data) to capture semantic meaning of companies, people, and signals for retrieval and ranking.
 </li>
 <li>
 Design and train ranking models that optimize search relevance, entity discovery, and lead recommendations across millions of entities.
 </li>
 <li>
 Build large-scale classification models to automatically tag industries, technologies, buyer intent, and other business signals.
 </li>
 <li>
 Deploy and monitor production ML pipelines for embedding generation, model inference, and continuous retraining with real-world feedback loops.
 </li>
 <li>
 Develop state-of-the-art supervised and semi-supervised models that scale to hundreds of millions of companies, professionals, and business signals.
 </li>
 <li>
 Own end-to-end model development and deployment of embeddings, retrieval, ranking, and classification models in large-scale production environments.
 </li>
 <li>
 Mentor junior ML engineers in applying advanced machine learning techniques to core problems such as entity resolution, lead scoring, and search relevance.
 </li>
 <li>
 Represent LinkedIn in academic and industry circles by showcasing our innovation, data products and scientific expertise in bringing game-changing data products to market
 
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 Basic Qualifications
 
 
 <ul>
 <li>
 Bachelor's degree or related practical experience
 </li>
 <li>
 2+ years of experience in at least one of the following areas: Recommendation systems, Machine Learning, Statistical modeling/inference, Data mining, Graph/geometric deep learning, Large Language Models, Generative AI, Distributed Training.
 
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Master's degree in computer science, statistics, engineering, mathematics, or similar quantitative discipline.
 </li>
 <li>
 3+ years of hands-on experience working on Recommendation systems, Machine Learning, Statistical modeling/inference, Data mining, Graph/geometric deep learning, Large Language Models, Generative AI, Distributed Training.
 </li>
 <li>
 Understanding of standard programming and software engineering practices
 </li>
 <li>
 Proven track record of publishing at academic and industry venues
 </li>
 <li>
 Ability and eagerness to program
 
 
 
 </li>
 </ul>
 Suggested Skills
 
 
 <ul>
 <li>
 Machine Learning
 </li>
 <li>
 Generative-AI
 </li>
 <li>
 Large Language Models
 
 
 
 </li>
 </ul>
 You will Benefit from our Culture
 
 
 We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels.
 
 
 
 Additional Information
 
 
 
 
 India Disability Policy
 
 
 
 LinkedIn is an equal employment opportunity employer offering opportunities to all job seekers, including individuals with disabilities. For more information on our equal opportunity policy, please visit https://legal.linkedin.com/content/dam/legal/Policy_India_EqualOppPWD_9-12-2023.pdf
 
 
 
 Global Data Privacy Notice for Job Candidates
 
 
 
 Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://legal.linkedin.com/candidate-portal.
 
 
</div>

Software Engineer, Machine Learning

HSBC

<div>
 
 Some Careers Have More Impact Than Others.
 
 
 
 If you&rsquo;re looking for a career where you can make a real impression, join HSBC and discover how valued you&rsquo;ll be.
 
 
 HSBC is one of the largest banking and financial services organisations in the world, with operations in 62 countries and territories. We aim to be where the growth is, enabling businesses to thrive and economies to prosper, and, ultimately, helping people to fulfil their hopes and realise their ambitions.
 
 
 We are currently seeking an experienced professional to join our team in the role of
 
 Machine Learning Data Scientist
 
 
 
 
 Business: Global Banking &amp; Markets
 
 
 
 
 Principal Responsibilities
 
 
 
 <ul>
 <li>
 The Role Holder will be responsible for leading the data science activities within the project, working with business analysts, data scientists and developers:
 </li>
 <li>
 Reviewing the proof of concept, current state and opportunities to utilise AI/ML in the Trade and Transaction Reporting Controls area.
 </li>
 <li>
 Proposing appropriate AI/ML models and techniques that will best fit with the data domains, volumes, available tools and business priorities.
 </li>
 <li>
 Using a range of AI/ML techniques and programming languages to transform data, analyse data and identify potential data quality issues.
 </li>
 <li>
 Building scalable machine learning pipelines and using feature engineering and optimisation methods to improve data set performance.
 </li>
 <li>
 Working with technology to integrate and separate data feeds to map, produce, transform and test new machine learning pipelines.
 </li>
 <li>
 Work with Business Partners to clarify problems/opportunities and propose solutions underpinned by strong data analysis of underlying controls and processes
 </li>
 <li>
 To understand and operate within HSBC&rsquo;s AI/ML governance and procedures
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Relevant Bachelor's or equivalent University degree in AI/Machine Learning.
 </li>
 <li>
 Evidence of a successful track record of leading delivery of AI/ML solutions within Markets/Investment Banks.
 </li>
 <li>
 Strong data scientist with experience in anomaly detection techniques, particularly in the trade data domain.
 </li>
 <li>
 Awareness of a broad range of ML techniques.
 </li>
 <li>
 Google Vertex an advantage.
 </li>
 <li>
 Good overall understanding of Primary Trading systems, trading products and front to back trade lifecycle flows.
 </li>
 <li>
 Demonstrated experience working with SMEs and key stakeholders to support understanding of the problem/data.
 </li>
 <li>
 Be capable of communicating complex data science/AI/ML techniques and processes to business users and SMEs
 </li>
 <li>
 Drive and resilience as must be comfortable working in rapidly changing and ambiguous situations.
 </li>
 <li>
 Hands on ability to perform data analysis to drive business insights and decision making.
 </li>
 <li>
 Proactive and willing to use own initiative to resolve issues.
 </li>
 <li>
 Excellent communication and interpersonal skills.
 </li>
 <li>
 Structured and methodical in planning their own book of work, delivery of artefacts, managing multiple competing priorities and setting expectations with stakeholders.
 
 
 </li>
 </ul>
 
 You&rsquo;ll achieve more at HSBC
 
 
 
 HSBC is an equal opportunity employer committed to building a culture where all employees are valued, respected and opinions count. We take pride in providing a workplace that fosters continuous professional development, flexible working and, opportunities to grow within an inclusive and diverse environment. We encourage applications from all suitably qualified persons irrespective of, but not limited to, their gender or genetic information, sexual orientation, ethnicity, religion, social status, medical care leave requirements, political affiliation, people with disabilities, color, national origin, veteran status, etc., We consider all applications based on merit and suitability to the role.&rdquo;
 
 
 Personal data held by the Bank relating to employment applications will be used in accordance with our Privacy Statement, which is available on our website.
 
 
 <ul>
 <li>
 Issued By HSBC Electronic Data Processing (India) Private LTD***
 </li>
 </ul>
</div>

Machine Learning Data Scientist (Blr)

Microsoft

<div>
 
 Come build community, explore your passions and do your best work at Microsoft with thousands of University interns from every corner of the world. This opportunity will allow you to bring your aspirations, talent, potential&mdash;and excitement for the journey ahead.
 
 
 
 Microsoft works with the world&rsquo;s best researchers, moving with the current of technology as it rapidly evolves. Together we share the motivation to seek innovative solutions to the world&rsquo;s toughest challenges and improve the lives of people everywhere.
 
 
 Microsoft provides a nurturing environment to support passionate researchers and engineers in AI technology innovation. We are seeking candidates excelling in deep thinking research aspects and fast-paced entrepreneurial execution. The ideal candidates should have the ability to work with researchers and product team colleagues at Microsoft to push forward research agendas, being a team player in a collaborative and supportive environment with outstanding programming skills.
 
 
 We are seeking candidates with research skills and technical backgrounds. Applicants should demonstrate depth of knowledge in Natural Language Understanding, Computer Vision, Machine Learning, Algorithmic Foundations of Optimization, Data Mining or Machine Intelligence (Artificial Intelligence) as well as strong academia experience in data processing, experimentation, and modeling.
 
 
 At Microsoft, Interns work on real-world projects in collaboration with teams across the world, while having fun along the way. You&rsquo;ll be empowered to build community, explore your passions and achieve your goals. This is your chance to bring your solutions and ideas to life while working on cutting-edge technology.
 
 
 
 Responsibilities
 
 
 
 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.
 
 
 <ul>
 <li>
 Analyze and improve performance of advanced algorithms on large-scale datasets and cutting-edge research in machine intelligence and machine learning applications.
 </li>
 <li>
 Implement prototypes of scalable systems in AI applications.
 </li>
 <li>
 Collaborate closely with team members on developing systems from prototyping to production level.
 </li>
 <li>
 Develop solutions for real world, large-scale problems.
 
 
 </li>
 </ul>
 MSR India conducts research in a wide range of areas and Internships are available in all of them. While the internships are offered year round, a majority of them begin in the summer. In the application process, we will try to find the opportunity that best aligns with your interests. During the internship, students are paired with mentors and expected to collaborate with other interns and researchers, present findings, and contribute to the vibrant life of the community. All internships are paid and we will help with visa applications where needed.
 
 
 
 Qualifications
 
 
 
 Required/Minimum Qualifications
 
 
 <ul>
 <li>
 Bachelor's Degree (complete or in progress) in relevant field
 </li>
 <li>
 OR Master's Degree in relevant field
 </li>
 <li>
 OR equivalent experience.
 
 
 </li>
 </ul>
 
 Additional Or Preferred Qualifications
 
 
 
 <ul>
 <li>
 Master's Degree or PhD in relevant field
 
 
 </li>
 </ul>
 OR equivalent experience.
 
 
 <ul>
 <li>
 Experience publishing academic papers as a lead author or essential contributor.
 </li>
 <li>
 Experience participating in a top conference in relevant research domain.
 
 
 </li>
 </ul>
 Microsoft is an equal opportunity employer. Consistent with applicable law, 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 and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.
</div>

Research Sciences Intern

Thinking Stack

<div>
 
 About The Role
 
 
 
 We&rsquo;re looking for highly motivated AI/ML Interns to work on impactful problems in Computer Vision, Natural Language Processing (NLP), LLMs, and Generative AI.
 
 
 This is a great opportunity for freshers or final-year students to gain real-world experience solving cutting-edge problems with deep learning.
 
 
 
 What You'll Do
 
 
 
 <ul>
 <li>
 Work on text classification, auto-regressive LLMs, and transformer models
 </li>
 <li>
 Develop models for image classification, object detection, segmentation, and OCR
 </li>
 <li>
 Apply SOTA (State-of-the-Art) techniques in Computer Vision and NLP
 </li>
 <li>
 Collaborate with senior AI engineers and researchers
 </li>
 <li>
 Contribute to building practical, scalable AI solutions
 
 
 </li>
 </ul>
 
 What We're Looking For
 
 
 
 <ul>
 <li>
 Strong Python skills and a deep interest in AI
 </li>
 <li>
 Hands-on experience with PyTorch, TensorFlow, scikit-learn, and OpenCV
 </li>
 <li>
 Basic understanding of LSTMs, Transformers, BERT, ResNet, etc.
 </li>
 <li>
 Exposure to real-world or academic projects in CV or NLP
 </li>
 <li>
 Self-motivated and eager to learn fast
 
 
 </li>
 </ul>
 
 Bonus Points For
 
 
 
 <ul>
 <li>
 Familiarity with Hugging Face Transformers, OpenAI APIs
 </li>
 <li>
 Prior work with OCR, object tracking, or auto-regressive models
 
 
 </li>
 </ul>
 
 Perks
 
 
 
 <ul>
 <li>
 Remote work flexibility
 </li>
 <li>
 Certificate upon completion
 </li>
 <li>
 Possible transition to a full-time role
 
 
 </li>
 </ul>
 
 Immediate joiners will be prioritized. Internship will be for (6-9 months)
 
 
 
 If you're a fresher looking to break into AI and contribute to real-world projects, we want to hear from you .
</div>

Data Science Intern

Wayfair

<div>
 
 
 Who We Are
 
 
 
 Wayfair&rsquo;s Advertising business is rapidly expanding, adding hundreds of millions of dollars in
 
 
 profits to Wayfair. We are building Sponsored Products, Display &amp; Video Ad offerings that cater
 
 
 to a variety of Advertiser goals while showing highly relevant and engaging Ads to millions of
 
 
 customers. We are evolving our Ads Platform to empower advertisers across all sophistication
 
 
 levels to grow their business on Wayfair at a strong, positive ROI and are leveraging state of the
 
 
 art Machine Learning techniques.
 
 
 
 
 
 The
 
 Advertising Optimization &amp; Automation Science
 
 team is central to this effort. We
 
 
 leverage machine learning and generative AI to streamline campaign workflows, delivering
 
 
 impactful recommendations on budget allocation, target Return on Ad Spend (tROAS), and SKU
 
 
 selection. Additionally, we are developing intelligent systems for creative optimization and exploring agentic frameworks to further simplify and enhance advertiser interactions.
 
 
 
 
 
 We are looking for seasoned ML Scientists to join the
 
 Advertising Optimization &amp; Automation Science
 
 team. In this role, you will be responsible for the development of budget, tROAS and SKU recommendations and other machine learning capabilities supporting our ads business. You will work closely with other scientists, as well as members of our internal Product and Engineering teams, to apply your engineering and machine learning skills to solve some of our most impactful and intellectually challenging problems to directly impact Wayfair&rsquo;s revenue.
 
 
 
 
 
 
 What you&rsquo;ll do
 
 
 <ul>
 <li>
 Provide technical leadership in the development of an automated and intelligent advertising system by advancing the state-of-the-art in machine learning techniques to support recommendations for Ads campaigns and other optimizations.
 </li>
 <li>
 Design, build, deploy and refine extensible, reusable, large-scale, and real-world platforms that optimize our ads experience.
 </li>
 <li>
 Work cross-functionally with commercial stakeholders to understand business problems or opportunities and develop appropriately scoped machine learning solutions
 </li>
 <li>
 Collaborate closely with various engineering, infrastructure, and machine learning platform teams to ensure adoption of best-practices in how we build and deploy scalable machine learning 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>
 Research new developments in advertising, sort and recommendations research and open-source packages, and incorporate them into our internal packages and systems.
 </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>
 
 
 
 
 
 What you&rsquo;ll need
 
 
 <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 advanced machine learning and statistical modeling, including hands-on designing and building production models at scale.
 </li>
 <li>
 Strong theoretical understanding of statistical models such as regression, clustering and machine learning algorithms such as decision trees, neural networks, etc.
 </li>
 <li>
 Familiarity with machine learning model development frameworks, machine learning orchestration and pipelines with experience in either Airflow, Kubeflow or MLFlow as well as Spark, Kubernetes, Docker, Python, and SQL.
 </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 written and verbal communication skills, ability to synthesize conclusions for non-experts, and overall bias towards simplicity
 </li>
 </ul>
 
 
 
 
 
 Nice to have
 
 
 <ul>
 <li>
 Familiarity with Machine Learning platforms offered by Google Cloud and how to implement them on a large scale (e.g. BigQuery, GCS, Dataproc, AI Notebooks).
 </li>
 <li>
 Experience in computational advertising, bidding algorithms, or search ranking
 </li>
 <li>
 Experience with deep learning frameworks like PyTorch, Tensorflow, etc.
 </li>
 </ul>
</div>

Lead Data Scientist

Nykaa

<div>
 
 
 About the Team:
 
 Join the dynamic Nykaa Data Science team as a Machine Learning Scientist II. In this role, you will contribute to analyzing data and developing machine learning models that enhance the relevance and ranking of our search platforms. You will work closely with cross-functional teams to gather performance metrics, evaluate search outcomes, and optimize the user experience on Nykaa's platform. This position offers the opportunity to collaborate in a fast-paced environment and make a significant impact on our search functionalities.
 
 
 What are we looking for ?
 
 
 
 Education
 
 :
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s Degree in Data Science, Computer Science, Statistics, or a related field from a reputable institution.
 </li>
 </ul>
 
 
 Experience
 
 :
 
 <ul>
 <li>
 3+ years of industry experience in Data Science and building Machine Learning models.
 </li>
 <li>
 Demonstrated experience in building and deploying machine learning models that handle large datasets.
 </li>
 <li>
 Experience in Search Data Science, Natural Language Processing (NLP) tasks, or Vector Search is a plus.
 </li>
 </ul>
 
 
 Technical Skills
 
 :
 
 <ul>
 <li>
 Strong foundational knowledge in Probability Theory, Statistics, and Machine Learning.
 </li>
 <li>
 Proficiency with machine learning languages and frameworks such as Python, Numpy, Pandas, Scikit-Learn, PySpark, TensorFlow/PyTorch, XGBoost/LightGBM.
 </li>
 <li>
 Understanding of A/B testing methodologies and experience in designing, implementing, and analyzing experiments to evaluate search algorithm performance.
 </li>
 <li>
 Familiarity with best practices throughout all stages of the Data Science lifecycle, including data preprocessing, model training, evaluation, deployment and monitoring.
 </li>
 </ul>
 
 
 Soft Skills
 
 :
 
 <ul>
 <li>
 Demonstrated ownership and ability to deliver results on data-driven projects.
 </li>
 <li>
 Capability to manage multiple priorities in a fast-paced environment.
 </li>
 <li>
 Technical aptitude to quickly gr/asp complex technical issues and communicate effectively with both technical and non-technical teams.
 </li>
 </ul>
 
 
 
 
 
 Responsibilities:
 
 
 <ul>
 <li>
 
 Search Optimization
 
 : Analyze user behavior insights in search and develop high-quality machine learning algorithms to improve search relevance and ranking.
 </li>
 <li>
 
 Model Development
 
 : Lead and mentor other machine learning scientists to promote learning, growth, and success within the team.
 </li>
 <li>
 
 Continuous Learning:
 
 Stay updated on advancements in the field of Machine Learning and apply these learnings to improve search algorithms.
 </li>
 <li>
 
 Customer Focus
 
 : Understand customer needs and leverage technology to enhance the search experience on Nykaa&rsquo;s platform.
 </li>
 <li>
 
 Documentation and Reporting
 
 : Document models, experiments, and processes. Present findings and insights to stakeholders to inform decision-making.
 </li>
 </ul>
 
 
</div>

ML Scientist II - Search

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