Data & Applied Scientist II Job at Microsoft Corporation (Redmond)

Data & Applied Scientist II

Are you a skilled Data Scientist with a passion for AI? Would you like to build ...

Location

Ireland , Dublin

Salary:

Not provided

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Do you have a degree (Bachelor’s, Master’s, or Doctorate) in a relevant quantitative field, or equivalent experience, along with the required level of data science experience?
Extensive experience with coding in SQL and R/Python/Spark to implement statistical models, machine learning, and analysis on big data
Deep knowledge of LLM/GPT fundamentals, and experience with prompt engineering, evaluation of LLM output, and agents
Outstanding written and oral communication, exemplified through experience in collaborative problem-solving, and presenting findings to technical and non-technical audiences
Extensive experience translating research or business problems into analytical, machine learning, and AI‑driven solutions
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Job Responsibility

Collaborate with cross‑functional partners to understand customer and product goals and contribute to growth in Microsoft 365 Copilot through the application of best practices in data science.
Translate business and customer problems into analytical, machine learning, causal modeling, and AI‑driven solutions by selecting and applying appropriate methodologies in Python and SQL.
Design, execute, and analyse A/B experiments by forming hypotheses, building scorecards, calculating new metrics, and interpreting results to inform product decisions.
Write efficient, readable, and maintainable production‑quality code and collaborate with engineering partners to integrate data models and analyses into Azure‑based systems.
Engage in AI research and development activities involving LLM fundamentals, prompt engineering, evaluation of LLM output, agents, and construction of LLM powered applications.
Evaluate model and analysis performance against business objectives by testing on real or production data, incorporating stakeholder feedback, and contributing to reviews of assumptions, risks, and limitations.
Learn and apply current data science, AI, privacy, security, and compliance best practices
engage with internal research and senior peers to share knowledge and contribute to scalable, responsible data‑driven solutions across Microsoft.

Fulltime

Applied Scientist II and Senior Applied Scientist

Come build community, explore your passions and do your best work at Microsoft. ...

Location

United States , Redmond

Salary:

100600.00 - 199000.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ years related experience (e.g., statistics, predictive analytics, research) 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) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field OR equivalent experience
2+ years experience delivering, scaling, and maintaining highly successful and innovative machine learning products
1+ year(s) experience creating publications (e.g., patents, peer-reviewed academic papers)
Experience with Large Language Models: Demonstrated experience working with LLMs, such as GPT, BERT, or similar models, including knowledge of their strengths, limitations, and capabilities
Understanding of NLP: In-depth knowledge of natural language processing (NLP) techniques and concepts, including tokenization, semantic analysis, and text generation
Understanding of state-of-the-art machine learning and deep learning technologies. In particular, hands-on experiences with deep learning models (DNN, Attention, CNN, RNN) and frameworks (TensorFlow, PyTorch, Keras, etc.)
Algorithmic and analytical background and understanding on how to apply advanced knowledge to solve real problems
Experience in parallel or distributed processing, high performance computing, stream computing and SCOPE

Job Responsibility

Building and maintaining production machine learning models for ad retrieval, quality prediction and creative generation
Finding insights and forming hypothesis on web-scale data with various machine learning, feature engineering, statistical, and data mining techniques: e.g. regression, classification, NLP, optimization, p-values analysis
Designing experiments, understanding the resulting data, and producing actionable, trustworthy conclusions from them
Craft and Optimize Prompts for Effective LLM Performance: Design, test, and refine prompts to elicit accurate, relevant, and useful responses from LLMs. This involves understanding the nuances of how the model interprets different inputs, experimenting with various prompt formulations, and iterating based on performance metrics and user feedback
Wrangling large amounts of data (think petabytes) using various tools, including open-source ones and your own. All programming languages are welcome, especially Python, R, C#, C++, Java, and SQL
Taking complex problems and the associated data and giving the answers in a concise form to assist senior executives in making key business decision

Fulltime

Applied Data Scientist II

Our team builds the intelligence layer that powers Microsoft’s next‑generation t...

Location

India , Bangalore

Salary:

Not provided

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Bachelor’s degree in CS, Data Science, EE, Mathematics or related field AND 6+ years of hands-on DS/ML experience
Strong proficiency in Python, ML frameworks (PyTorch/TensorFlow), and data processing libraries
Experience with ML techniques such as: gradient-boosted models, supervised/unsupervised learning, embeddings, clustering, anomaly detection
Experience querying & analyzing large datasets using Kusto, SQL, Spark, or equivalent data engines
Strong fundamentals in probability, statistics, and algorithmic thinking
Ability to write clean, reliable research code and communicate findings clearly.

Job Responsibility

Develop supervised and unsupervised ML models for anomaly detection, fraud/threat pattern discovery, alert classification, confidence scoring, and signal fidelity improvements
Build and maintain feature pipelines over multi-modal security telemetry (identity, endpoint, network, cloud)
Apply graph-focused ML techniques (graph embeddings, GNNs, similarity scoring, relationship modeling)
Contribute to graph construction logic, schema evolution, and ontology-driven enrichment for Verdict Net, Verdict Propagation, Campaign Graphs, and Vortex insights
Implement graph traversal, multi-hop reasoning, and cluster detection algorithms to surface hidden attack patterns
Participate in performance optimization and health management of large-scale threat graphs
Analyze large, noisy, high-dimensional security datasets using ADX/Kusto, Spark, and distributed compute platforms
Run A/B experiments, offline evaluations, and benchmark models to continually improve detection quality
Build high-quality research code and prototypes that transition smoothly to engineering teams for productionization
Collaborate with detection engineering, threat research, product teams and red teams to integrate ML outcomes into real-world protection experiences

Fulltime

Applied Data Scientist II

Our team builds the intelligence layer that powers Microsoft’s next‑generation s...

Location

India , Hyderabad

Salary:

Not provided

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Bachelor’s degree in CS, Data Science, EE, Mathematics or related field AND 4+ years of hands-on DS/ML experience OR Master’s degree AND 1+ years experience
Strong proficiency in Python, ML frameworks (PyTorch/TensorFlow), and data processing libraries
Experience with ML techniques such as: gradient-boosted models, supervised/unsupervised learning, embeddings, clustering, anomaly detection
Experience querying & analyzing large datasets using Kusto, SQL, Spark, or equivalent data engines
Strong fundamentals in probability, statistics, and algorithmic thinking
Ability to write clean, reliable research code and communicate findings clearly

Job Responsibility

Machine Learning & Modeling: Develop supervised and unsupervised ML models for anomaly detection, fraud/threat pattern discovery, alert classification, confidence scoring, and signal fidelity improvements
Build and maintain feature pipelines over multi-modal security telemetry (identity, endpoint, network, cloud)
Apply graph-focused ML techniques (graph embeddings, GNNs, similarity scoring, relationship modeling)
Graph Reasoning & Analytics: Contribute to graph construction logic, schema evolution, and ontology-driven enrichment for Verdict Net, Verdict Propagation, Campaign Graphs, and Vortex insights
Implement graph traversal, multi-hop reasoning, and cluster detection algorithms to surface hidden attack patterns
Participate in performance optimization and health management of large-scale threat graphs
Data Engineering & Experimentation: Analyze large, noisy, high-dimensional security datasets using ADX/Kusto, Spark, and distributed compute platforms
Run A/B experiments, offline evaluations, and benchmark models to continually improve detection quality
Build high-quality research code and prototypes that transition smoothly to engineering teams for productionization
Cross-Functional Impact: Collaborate with detection engineering, threat research, product teams and red teams to integrate ML outcomes into real-world protection experiences

Fulltime

Applied Scientist II

Alexa International is looking for passionate, talented, and inventive Senior Ap...

Location

India , Bengaluru

Salary:

Not provided

Amazon Pforzheim GmbH

Expiration Date

Until further notice

Requirements

3+ years of building models for business application experience
PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
Experience in patents or publications at top-tier peer-reviewed conferences or journals
Experience programming in Java, C++, Python or related language
Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

Job Responsibility

Analyze, understand, and model customer behavior and the customer experience based on large-scale data
Build novel online & offline evaluation metrics and methodologies for multimodal personal digital assistants
Fine-tune/post-train LLMs using advanced and innovative techniques like SFT, DPO, Reinforcement Learning (RLHF and RLAIF) for supporting model performance specific to a customer’s location and language
Quickly experiment and set up experimentation framework for agile model and data analysis or A/B testing
Contribute through industry-first research to drive innovation forward
Drive cross-team scientific strategy and influence partner teams on LLM evaluation frameworks, post-training methodologies, and best practices for international speech and language systems
Lead end-to-end delivery of scientifically complex solutions from research to production, including reusable science components and services that resolve architecture deficiencies across teams
Serve as a scientific thought leader, communicating solutions clearly to partners, stakeholders, and senior leadership
Actively mentor junior scientists and contribute to the broader internal and external scientific community through publications and community engagement

Fulltime

Data Scientist II

Location

United States , Chicago

Salary:

130000.00 - 150000.00 USD / Year

Arrive Logistics

Expiration Date

Until further notice

Requirements

Bachelor’s or Master’s degree in a quantitative field (computer science, statistics, linguistics, or related) and 2–4 years of applied ML or data science experience, or equivalent practical experience
Hands-on experience building or improving NLP or LLM-based systems in applied settings
Familiarity with text classification, information extraction, or other NLP tasks — and an understanding of where these systems fail
Experience with both prompt engineering and fine-tuning approaches for language tasks, with the judgment to know when to apply each
Familiarity with modern retrieval strategies and RAG architectures and how they affect LLM system performance
Experience with Hugging Face Transformers for text classification or related NLP tasks
Experience contributing to evaluation frameworks, test sets, or performance diagnostics for ML systems, including comfort with statistical methods for measuring model performance
Proficiency in Python and SQL, and comfort working with structured and unstructured data
Ability to operate effectively in ambiguous problem spaces — scoping technical approaches when requirements are not fully defined
Strong written communication skills

Job Responsibility

Develop, evaluate, and iterate on NLP and LLM-based systems, including text classification, information extraction, and context retrieval pipelines
Build measurement and evaluation frameworks — both offline and online — to assess where and why systems are underperforming and quantify the impact of improvements
Develop golden test datasets and define methodologies for creating and maintaining them over time, including designing annotation guidelines and ensuring label quality
Evaluate and apply the appropriate approach for language tasks — whether prompt engineering, fine-tuning, or classical NLP methods — including modern retrieval and RAG architectures and LLM evaluation methodologies, based on the problem and available data
Perform structured analysis of system performance to surface failure modes, data gaps, and high-value areas for investment, applying sound statistical reasoning to evaluation results
Partner with engineers to support deployment, integration, and monitoring of ML and AI systems in production
Contribute to standards and best practices around deploying, evaluating, and monitoring text and language-based ML systems
Document work clearly and maintain knowledge artifacts that make systems understandable and maintainable over time
Collaborate with senior data scientists and cross-functional partners to translate business needs into well-scoped technical solutions, including communicating findings and recommendations to non-technical stakeholders

What we offer

Medical, dental, vision, life, disability, and supplemental coverage
Matching 401(k) program
Employee Resource Groups
Office wide engagement activities, team events, happy hours
Casual dress code
Work in downtown Chicago, IL
LifeStart gym with Peloton bikes and personal training
Free counseling sessions through Employee Assistance Program
Company paid holidays, paid vacation time and wellness days
100% paid parental leave

Fulltime

Data Scientist II

Arrive Logistics is a leading transportation and technology company in North Ame...

Location

United States , Austin

Salary:

Not provided

Arrive Logistics

Expiration Date

Until further notice

Requirements

Bachelor’s or Master’s degree in a quantitative field (computer science, statistics, linguistics, or related) and 2–4 years of applied ML or data science experience, or equivalent practical experience
Hands-on experience building or improving NLP or LLM-based systems in applied settings
Familiarity with text classification, information extraction, or other NLP tasks — and an understanding of where these systems fail
Experience with both prompt engineering and fine-tuning approaches for language tasks, with the judgment to know when to apply each
Familiarity with modern retrieval strategies and RAG architectures and how they affect LLM system performance
Experience with Hugging Face Transformers for text classification or related NLP tasks
Experience contributing to evaluation frameworks, test sets, or performance diagnostics for ML systems, including comfort with statistical methods for measuring model performance
Proficiency in Python and SQL, and comfort working with structured and unstructured data
Ability to operate effectively in ambiguous problem spaces — scoping technical approaches when requirements are not fully defined
Strong written communication skills

Job Responsibility

Develop, evaluate, and iterate on NLP and LLM-based systems, including text classification, information extraction, and context retrieval pipelines
Build measurement and evaluation frameworks — both offline and online — to assess where and why systems are underperforming and quantify the impact of improvements
Develop golden test datasets and define methodologies for creating and maintaining them over time, including designing annotation guidelines and ensuring label quality
Evaluate and apply the appropriate approach for language tasks — whether prompt engineering, fine-tuning, or classical NLP methods — including modern retrieval and RAG architectures and LLM evaluation methodologies, based on the problem and available data
Perform structured analysis of system performance to surface failure modes, data gaps, and high-value areas for investment, applying sound statistical reasoning to evaluation results
Partner with engineers to support deployment, integration, and monitoring of ML and AI systems in production
Contribute to standards and best practices around deploying, evaluating, and monitoring text and language-based ML systems
Document work clearly and maintain knowledge artifacts that make systems understandable and maintainable over time
Collaborate with senior data scientists and cross-functional partners to translate business needs into well-scoped technical solutions, including communicating findings and recommendations to non-technical stakeholders

What we offer

Comprehensive benefits package, including medical, dental, vision, life, disability, and supplemental coverage
Matching 401(k) program
Employee Resource Groups
Office wide engagement activities, team events, happy hours and more
Casual dress code
Work in the booming city of Austin, TX – we are in a convenient location close to the airport and downtown
Free on-site parking
Fully stocked coffee bar, Broker’s Brew
Onsite gym
Free counseling sessions through our Employee Assistance Program

Fulltime

Applied Scientist II, Demand Science

The Amazon Devices & Services Demand Science (DSci) team is seeking a scientist ...

Location

United States , Seattle

Salary:

142800.00 - 193200.00 USD / Year

Amazon Pforzheim GmbH

Expiration Date

Until further notice

Requirements

4+ years of building models for business application experience
PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
Experience programming in Java, C++, Python or related language
Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning
Experience in building machine learning models for business application

Job Responsibility

Build forecasting models from prototype through production, working closely with engineering to deploy at scale
Find and integrate new data sources to improve forecast accuracy and coverage
Design and deliver production-ready solutions for business-critical forecasting and optimization problems
Define and track performance metrics — both technical (error rates, bias, coverage) and business (plan attainment, financial impact, reduction in manual overrides)
Write and maintain clear technical documentation
present findings and recommendations to scientists, engineers, and business leaders
Set team standards for methodology, code quality, experimentation rigor, and AI-assisted workflows

What we offer

health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
401(k) matching
paid time off
parental leave
sign-on payments
restricted stock units (RSUs)

Fulltime

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Data & Applied Scientist II

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