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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>
 </ul>
 
 
</div>

Data Scientist

LSEG

<div>
 Proud to share LSEG in the India is Great Place to Work certified (Jun &rsquo;25 &ndash; Jun &rsquo;26).
 
 
 Learn more about life and purpose of our company directly from India colleagues&rsquo; video: Bengaluru, India | Where We Work | LSEG
 
 
 
 Headline :
 
 Builds and uses data science knowledge and expertise, supporting projects and building data science products and solutions.
 
 
 
 Role Responsibilities &amp; Key Accountabilities:
 
 
 
 <ul>
 <li>
 Supports projects, leveraging technical expertise to remove obstacles and to find creative solutions.
 </li>
 <li>
 Builds data science products and solutions utilising data science techniques directly.
 </li>
 <li>
 Creates compelling proposals with technologists and business to drive innovation from conception to production with appropriate success metrics.
 </li>
 <li>
 Builds and uses domain expertise in financial market content, data science and LSEG data and products.
 </li>
 <li>
 Writes highly optimised code for LSEG products and solutions.
 
 
 </li>
 </ul>
 Qualifications &amp; Experience:
 
 
 <ul>
 <li>
 Degree or equivalent
 </li>
 <li>
 Moderate experience in a data science related role
 
 
 </li>
 </ul>
 
 Job Description
 
 
 
 The Fixed Income Reference team collects, manages, and supplies content related to Bonds . This content is used extensively across by clients and beyond Refinitiv/LSEG and is a critical asset to a wide range of Refinitiv/LSEG products.
 
 
 
 The role of the Data Scientist is to:
 
 
 
 Design and develop new methodologies, quantitative models, analysis and commentary (as relevant) that enhance existing or new processes. Maintain existing product performance and independent analysis standards. Internally, work with various departments to grow new ideas and expand the scope of existing products.
 
 
 
 Essential Day-to-Day Responsibilities:
 
 
 
 <ul>
 <li>
 Data handling, data processing and programming
 </li>
 <li>
 Develop automated solutions for sourcing/loading Fixed Income Reference data into Database
 </li>
 <li>
 Analyze Fixed Income Reference content to establish patterns/trends
 </li>
 <li>
 Develop, improve and run quantitative models
 </li>
 <li>
 Generate solutions through AI &amp; machine learning for core processes
 </li>
 <li>
 Work with business, content and product groups for large-scale analytics problems
 </li>
 <li>
 Build POCs, visualizations and pipeline tools for product design and development
 </li>
 <li>
 Work with development groups for deployment of analytics solutions
 </li>
 <li>
 Interact with other internal teams as needed, with supervision.
 
 
 </li>
 </ul>
 
 Knowledge &amp; Skills:
 
 
 
 <ul>
 <li>
 Understanding of algorithms, model building, and evaluation
 </li>
 <li>
 Strong understanding of machine learning algorithms
 </li>
 <li>
 Knowledge of neural networks and deep learning frameworks
 </li>
 <li>
 Extensive experience using Python or R or equivalent
 </li>
 <li>
 Skills in transforming and preparing data for model training
 </li>
 <li>
 Proficient in using tools and libraries such as scikit-learn, numpy, pandas and jupyter
 </li>
 <li>
 Solid relational database skills
 </li>
 <li>
 Solid understanding of statistics and statistical language such as R
 </li>
 <li>
 Ability to handle large quantities of data
 </li>
 <li>
 Narrate stories (to technical and mostly non-technical audience) about our content and processes by data analysis and visualization
 </li>
 <li>
 Strong written, communication and presentation skills. Able to respond and present work to peers, senior management and other stakeholders
 
 
 </li>
 </ul>
 
 Qualification:
 
 
 
 Higher education in Statistics, Mathematics or Engineering in Computer Science with Data science certification
 
 
 Join us and be part of a team that values innovation, quality, and continuous improvement. If you're ready to take your career to the next level and make a significant impact, we'd love to hear from you.
 
 
 LSEG is a leading global financial markets infrastructure and data provider. Our purpose is driving financial stability, empowering economies and enabling customers to create sustainable growth.
 
 
 Our purpose is the foundation on which our culture is built. Our values of
 
 Integrity, Partnership
 
 ,
 
 Excellence
 
 and
 
 Change
 
 underpin our purpose and set the standard for everything we do, every day. They go to the heart of who we are and guide our decision making and everyday actions.
 
 
 Working with us means that you will be part of a dynamic organisation of 25,000 people across 65 countries. However, we will value your individuality and enable you to bring your true self to work so you can help enrich our diverse workforce.
 
 
 We are proud to be an equal opportunities employer. This means that we do not discriminate on the basis of anyone&rsquo;s race, religion, colour, national origin, gender, sexual orientation, gender identity, gender expression, age, marital status, veteran status, pregnancy or disability, or any other basis protected under applicable law. Conforming with applicable law, we can reasonably accommodate applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs.
 
 
 You will be part of a collaborative and creative culture where we encourage new ideas. We are committed to sustainability across our global business and we are proud to partner with our customers to help them meet their sustainability objectives. Our charity, the LSEG Foundation provides charitable grants to community groups that help people access economic opportunities and build a secure future with financial independence. Colleagues can get involved through fundraising and volunteering.
 
 
 LSEG offers a range of tailored benefits and support, including healthcare, retirement planning, paid volunteering days and wellbeing initiatives.
 
 
 Please take a moment to read this privacy notice carefully, as it describes what personal information London Stock Exchange Group (LSEG) (we) may hold about you, what it&rsquo;s used for, and how it&rsquo;s obtained, your rights and how to contact us as a data subject.
 
 
 If you are submitting as a Recruitment Agency Partner, it is essential and your responsibility to ensure that candidates applying to LSEG are aware of this privacy notice.
</div>

Google

<div>
 
 Minimum qualifications:
 
 
 
 <ul>
 <li>
 Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
 </li>
 <li>
 2 years of experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL) (or experience with a Master's degree).
 
 
 </li>
 </ul>
 
 Preferred qualifications:
 
 
 
 <ul>
 <li>
 Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
 </li>
 <li>
 3 years of work experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL).
 
 
 </li>
 </ul>
 
 About The Job
 
 
 
 Help serve Google's worldwide user base of more than a billion people. Data Scientists provide quantitative support, market understanding and a strategic perspective to our partners throughout the organization. As a data-loving member of the team, you serve as an analytics expert for your partners, using numbers to help them make better decisions. You will weave stories with meaningful insight from data. You'll make critical recommendations for your fellow Googlers in Engineering and Product Management. You relish tallying up the numbers one minute and communicating your findings to a team leader the next.
 
 
 To accelerate the growth and market leadership of Enterprise Buying Platforms (DV360 and SA360) by answering critical business questions and delivering actionable, data-driven insights that inform product and commercial strategy. The Enterprise Platform Data Science Team provides quantitative support, market understanding and a strategic perspective to our partners throughout the organization, in close collaboration with the Ads and Commerce Finance team.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Execute defined, moderately difficult investigative tasks under guidance from the manager or executive team member/team lead. For straightforward problems, execute end-to-end analysis with minimal guidance.
 </li>
 <li>
 Manage workload to reflect the priorities set by the team, work towards a timeline, and communicate slippage.
 </li>
 <li>
 Select appropriate approaches from clear options to address technical challenges under some guidance from managers or executive team members. Plan out analyses (as opposed to trial and error approach).
 </li>
 <li>
 Break down broader tasks into components and anticipate complexities/blockers.
 
 
 
 </li>
 </ul>
 Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .
</div>

Data Scientist, Enterprise Platform

Amadeus

<div>
 
 Job Title
 
 
 
 Data Scientist 3
 
 
 
 About The Role
 
 
 
 You will join a multidisciplinary team of software engineers, data engineers, data scientists, product specialists, and designers working on next-generation
 
 AI-powered solutions
 
 for airport and airline operations. As part of the Data Spark
 
 Agile Release Train
 
 , you will collaborate closely with colleagues in Nice and London.
 
 
 Your key responsibility will be to
 
 design, automate, and optimize machine learning workflows
 
 that power:
 
 
 <ul>
 <li>
 Real-time analytics and inferencing
 </li>
 <li>
 Predictive modeling
 </li>
 <li>
 ML foundations for generative AI capabilities
 
 
 </li>
 </ul>
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Lead the design, implementation, and maintenance of scalable, cloud-native ML pipelines (primarily on Microsoft Azure within a multi-cloud strategy) for batch and streaming workloads.
 </li>
 <li>
 Automate the end-to-end lifecycle of ML models: data preparation, experimentation, tuning, deployment, monitoring, and continuous improvement with a focus on reproducibility and governance.
 </li>
 <li>
 Collaborate with software engineers to ensure robust integration of ML models into production systems, including API contracts, SLAs, fallbacks, and graceful degradation strategies.
 
 
 </li>
 </ul>
 
 About The Ideal Candidate
 
 
 
 <ul>
 <li>
 Proven experience building and maintaining production-grade ML pipelines in cloud environments across real-world projects.
 </li>
 <li>
 Strong hands-on experience with ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch) and solid understanding of model development patterns (supervised learning, time-series forecasting, model evaluation).
 </li>
 <li>
 Practical MLOps expertise with tools like Azure Machine Learning, MLflow, or similar platforms for experiment tracking, pipeline orchestration, and model deployment.
 </li>
 <li>
 Strong command of Python for production-grade deliveries, including testing, code reviews, documentation, packaging, and version control.
 </li>
 <li>
 Experience working in Agile teams (Scrum, SAFe).
 
 
 </li>
 </ul>
 
 
 
 Diversity &amp; Inclusion
 
 
 
 
 
 Amadeus aspires to be a leader in Diversity, Equity and Inclusion in the tech industry, enabling every employee to reach their full potential by fostering a culture of belonging and fair treatment, attracting the best talent from all backgrounds, and as a role model for an inclusive employee experience.
 
 
 Amadeus is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to gender, race, ethnicity, sexual orientation, age, beliefs, disability or any other characteristics protected by law.
</div>

Data Scientist 3

Syngene International Limited

<div>
 Date: 18 Dec 2025
 
 
 Location:
 
 
 Bangalore, KA, IN, 560099
 
 
 Division: Development Services
 
 
 
 Job Description
 
 
 
 Designation: Formulation Scientist
 
 
 Job Location: Bangalore
 
 
 The Company
 
 
 Syngene International Ltd. (BSE: 539268, NSE: SYNGENE, ISIN: INE398R01022), is an integrated research, development, and manufacturing solutions company serving the global pharmaceutical, biotechnology, nutrition, animal health, consumer goods, and specialty chemical sectors. Syngene&rsquo;s 4500+ scientists offer both the skills and capacity to deliver great science, robust data management and IP security, and quality manufacturing at speed, to improve time-to-market and lower the cost of innovation. With a combination of 1.9 Mn sq ft of specialist discovery, development and manufacturing facilities, as well as dedicated research facilities for Amgen, Baxter, Bristol-Myers Squibb and Herbalife, Syngene works with biotech companies pursuing leading edge science as well as multinationals including GSK and Merck KGaA.
 
 
 Key Result Areas
 
 
 
 Role-specific
 
 
 
 
 Functional Responsibilities:
 
 
 
 <ul>
 <li>
 Design and develop parenteral formulations for complex biologics
 </li>
 <li>
 Execute pre-formulation studies of biologics through rational design principles including structure function assessment, buffer/excipient/stabilizer screening, etc.
 </li>
 <li>
 Plan and execute drug substance/product stability studies, analyze data trend and support assessment of degradation kinetics and assign shelf-life.
 </li>
 <li>
 Author protocols, technical reports and communicate studies outcome to cross-functional groups.
 
 
 </li>
 </ul>
 
 Primary Responsibilities
 
 
 
 <ul>
 <li>
 Should have a strong background in Biologics Parenteral Formulation development including solid and liquid dosage forms
 </li>
 <li>
 Experience in both early and late formulation development of mAbs and fusion proteins
 </li>
 <li>
 Good knowledge on Formulation and Process characterization studies
 </li>
 <li>
 Experienced in handling instruments like Density meter / Osmometer / Viscometer / Turbidity meter / UV Spectrophotometer / HPLC systems
 </li>
 <li>
 Ability to learn quickly, enthusiastic, sincere, positive attitude, hardworking
 </li>
 <li>
 Should have positive temperament, rational/logical thinking and enthusiasm to deliver on time, hardworking and committed.
 </li>
 <li>
 Basic understanding of statistics, DoE and data visualization
 </li>
 <li>
 Should be experienced/demonstrated formulation and process characterization.
 </li>
 <li>
 Authoring Technical documents like PDR, Tech transfer, study reports etc.
 
 
 </li>
 </ul>
 
 Education
 
 
 
 <ul>
 <li>
 M.Pharm or M.Sc. in Life Science/Biotechnology/ Bioprocess Engineering/ Pharmaceuticals/Biopharmaceuticals/ Biopharmaceutical Technology/ Biochemistry or equivalent degree.
 
 
 </li>
 </ul>
 
 Industry Experience
 
 
 
 <ul>
 <li>
 Minimum 6-9 years of relevant practical experience in formulation development for biopharmaceuticals, specifically with mAbs, Proteins and peptides.
 
 
 </li>
 </ul>
 Equal Opportunity Employer
 
 
 It is the policy of Syngene to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by applicable legislation or local law. In addition, Syngene will provide reasonable accommodations for qualified individuals with disabilities.
 
 
 Pls visit us at https://syngeneintl.com/ to know more about us and what we do.
</div>

Formulation 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>

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

Explore 357+ Data science specialist in Mangaluru India this January. Find roles across top companies and apply now to boost your career.

357 data science specialist jobs IN Mangaluru India

Data Scientist

Data Scientist

Data Scientist, Enterprise Platform

Data Scientist 3

Formulation Scientist

Data Scientist

Data & Applied Scientist II