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machine learning software engineer

Microsoft

<div>
 
 Overview
 
 
 
 As a Member of Technical Staff - Software Engineer &amp; Machine Learning, you will work building AI Insights, a Copilot analytics product that enables our internal stakeholders to move from &ldquo;What happened?&rdquo; to &ldquo;Why did it happen?&rdquo; in minutes. You&rsquo;ll design and implement AI-driven trend detection, cohort analysis, and drill-down workflows that connect metrics to real user conversations. n developing AI based insights on large scale multi modal Copilot data part of the Microsoft AI (MAI) organization. We&rsquo;re looking for a experienced Machine Learning engineer with strong hands-on skills in machine learning, data platforms, and distributed systems to lead the development of AI Insights, a next-generation Copilot analytics product. The right candidate takes the initiative and enjoys building world-class consumer experiences and products in a fast-paced environment.
 
 
 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.
 
 
 Starting January 26, 2026, MAI employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location. This expectation is subject to local law and may vary by jurisdiction.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Build scalable data pipelines for telemetry ingestion, anomaly detection, and cohort segmentation.
 </li>
 <li>
 Implement ML-driven insights (prompted classifiers, anomaly detection) and integrate them into dashboards and APIs.
 </li>
 <li>
 Develop secure, compliant workflows for handling production logs and conversation data.
 </li>
 <li>
 Enable drill-down capabilities linking quantitative metrics to qualitative evidence for actionable context.
 </li>
 <li>
 Collaborate with PMs and DS to refine hypotheses and deliver intuitive, high-performance interfaces.
 </li>
 <li>
 Own technical strategy for trend detection, cohort analysis, and drill-down workflows linking quantitative metrics to qualitative conversation evidence.
 </li>
 <li>
 Prototype and productionize ML models for anomaly detection and predictive insights.
 </li>
 <li>
 Ensure compliance and security for data handling across telemetry, logs, and conversation datasets.
 </li>
 <li>
 Collaborate with PMs, data scientists, and UX to define roadmap and deliver intuitive, high-impact workflows.
 </li>
 <li>
 Independently write efficient, readable, extensible code and model pipelines.
 </li>
 <li>
 Commit to a customer-oriented focus by acknowledging customer needs and perspectives, validating customer perspectives, focusing on broader customer context, and serving as a trusted advisor.
 </li>
 <li>
 Hands-on with observability (metrics, tracing, logs) and model evaluation frameworks.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 
 Required Qualifications:
 
 
 
 <ul>
 <li>
 Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
 </li>
 <ul>
 <li>
 OR equivalent experience.
 
 </li>
 </ul>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
 </li>
 <ul>
 <li>
 OR Bachelor's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
 </li>
 </ul>
 <li>
 Proven experience leading small engineering and machine learning teams, and collaborating effectively with cross-functional stakeholders including product managers, UX designers, and security specialists.
 </li>
 <li>
 Demonstrated interest in Responsible AI.
 
 </li>
 </ul>
 #MicrosoftAI
 
 
 Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $139,900 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.
 
 
 Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
 
 
 https://careers.microsoft.com/us/en/us-corporate-pay
 
 
 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>

Machine Learning Software Engineer

Microsoft AI

Mount Sinai Health System

<div>Description
The Windreich Department of AI &amp; Human Health is rapidly advancing the use of technology to improve health outcomes and is at the forefront of AI implementation within the Mount Sinai Health.
Machine Learning Engineer III will oversee the design and development of sophisticated machine learning systems. They will collaborate closely with cross-functional teams to drive innovation and ensure the successful implementation of machine learning solutions. 
Responsibilities
End-to-End System Responsibility:<ul><li>
Assume complete ownership of the entire machine learning system development process.</li><li>
Coordinate closely with other team members and other engineering teams to ensure seamless integration and alignment with broader organizational goals and workflows.</li><li>
Lead the collaborative efforts with cross-functional teams, including data scientists and product managers, to ensure the successful deployment and robust maintenance of machine learning models.</li><li>
Oversee the continuous monitoring and timely updating of deployed models to guarantee enduring performance and reliability.</li></ul>
Technical Leadership:<ul><li>
Exhibit technical leadership and mentorship to Machine Learning Engineer I, II, and other team members.</li><li>
Encourage knowledge exchange and promote professional growth within the team.</li><li>
Establish and enforce best practices for machine learning system development, including coding standards, code reviews, and comprehensive documentation.</li><li>
Serve as the primary contact for technical inquiries related to machine learning within the team, providing expert guidance and solutions.</li></ul>
Problem-Solving:<ul><li>
Utilize advanced problem-solving skills to navigate and resolve complex technical challenges and obstacles.</li><li>
Foster a collaborative environment for brainstorming and implementing effective solutions with the team and other departments.</li></ul>
Research and Development:<ul><li>
Remain up-to-date with the latest advancements and trends in the fields of software engineering and machine learning.</li><li>
Conduct proactive research to uncover new methods and techniques applicable to future projects.</li><li>
Lead initiatives to explore, test, and implement new technologies and frameworks, ensuring the team is always at the forefront of industry innovations.</li></ul>
Collaboration and Communication:<ul><li>
Engage in effective communication and collaboration across various teams within the organization to ensure alignment and coordination in the execution of machine learning projects.</li><li>
Facilitate transparent and timely communication with all relevant stakeholders, ensuring that all are kept informed of project statuses, challenges, and achievements.</li><li>
Work collaboratively with cross-functional teams, fostering a cooperative environment for the seamless integration of machine learning systems into diverse organizational processes and workflows.</li><li>
Contribute to building strong interdepartmental relationships, enabling the efficient exchange of knowledge and expertise, and ensuring the successful realization of machine learning initiatives.</li></ul>
Additional Responsibilities:<ul><li>
Develop and maintain project work plans, including critical tasks, milestones, timelines, interdependencies, and contingencies. Tracks and reports progress. Keeps stakeholders apprised of project status and implications for completion.</li><li>
Prepare clear, well-organized project-specific documentation, including, at a minimum, analytic methods used, key decision points and caveats, with sufficient detail to support comprehension and replication.</li><li>
Mentor other analysts on how to a) determine appropriate statistical analysis methods, b) leverage appropriate programing languages and tools, and c) generate and interpret statistical analysis outputs.</li><li>
Share development and process knowledge with other analysts in order to assure redundancy and continuously builds a core of analytical strength within the organization.</li><li>
Adheres to corporate standards for performance metrics, data collection, data integrity, query design, and reporting format to ensure high quality, meaningful analytic output.</li><li>
Works closely with IT on the ongoing improvement of Mount Sinai&rsquo;s integrated data warehouse, driven by strategic and business needs, and designed to ensure data and reporting consistency throughout the organization.</li><li>
Demonstrates advanced level proficiency with the principles and methodologies of process improvement. Applies these in the execution of responsibilities in support of a process focused approach.</li><li>
Other duties as assigned.</li></ul> 

Qualifications<ul><li>
Bachelor&rsquo;s degree in Computer Science, Data Science, or a related field.</li><li>
4+ years of relevant experience in machine learning and back-end software development.</li><li>
Demonstrated end-to-end machine learning system development and operation experience, covering the complete Software Development Life Cycle (SDLC).</li><li>
Proficiency in multiple programming languages and machine learning frameworks and tools.</li><li>
Solid experience with both SQL and NoSQL databases.</li><li>
Extensive experience with Big Data technologies like Apache Spark.</li><li>
Hands-on experience in Unix environments.</li><li>
Practical knowledge and experience with at least one cloud system among AWS, Azure, or Google Cloud.</li><li>
Familiarity with continuous development and integration systems such as Jenkins, Git, Azure DevOps, and Terraform.</li><li>
A proven history in developing, deploying, and operating efficient and reliable machine learning systems.</li><li>
Strong leadership and effective communication skills to facilitate cross-functional collaboration throughout the organization.</li><li>
Experience in providing mentorship</li></ul> 
Employer Description
Strength through Unity and Inclusion

The Mount Sinai Health System is committed to fostering an environment where everyone can contribute to excellence. We share a common dedication to delivering outstanding patient care. When you join us, you become part of Mount Sinai&rsquo;s unparalleled legacy of achievement, education, and innovation as we work together to transform healthcare. We encourage all team members to actively participate in creating a culture that ensures fair access to opportunities, promotes inclusive practices, and supports the success of every individual.

At Mount Sinai, our leaders are committed to fostering a workplace where all employees feel valued, respected, and empowered to grow. We strive to create an environment where collaboration, fairness, and continuous learning drive positive change, improving the well-being of our staff, patients, and organization. Our leaders are expected to challenge outdated practices, promote a culture of respect, and work toward meaningful improvements that enhance patient care and workplace experiences. We are dedicated to building a supportive and welcoming environment where everyone has the opportunity to thrive and advance professionally. Explore this opportunity and be part of the next chapter in our history.

About the Mount Sinai Health System:

Mount Sinai Health System is one of the largest academic medical systems in the New York metro area, with more than 48,000 employees working across eight hospitals, more than 400 outpatient practices, more than 300 labs, a school of nursing, and a leading school of medicine and graduate education. Mount Sinai advances health for all people, everywhere, by taking on the most complex health care challenges of our time &mdash; discovering and applying new scientific learning and knowledge; developing safer, more effective treatments; educating the next generation of medical leaders and innovators; and supporting local communities by delivering high-quality care to all who need it. Through the integration of its hospitals, labs, and schools, Mount Sinai offers comprehensive health care solutions from birth through geriatrics, leveraging innovative approaches such as artificial intelligence and informatics while keeping patients&rsquo; medical and emotional needs at the center of all treatment. The Health System includes more than 9,000 primary and specialty care physicians; 13 joint-venture outpatient surgery centers throughout the five boroughs of New York City, Westchester, Long Island, and Florida; and more than 30 affiliated community health centers. We are consistently ranked by U.S. News &amp; World Report's Best Hospitals, receiving high &quot;Honor Roll&quot; status, and are highly ranked: No. 1 in Geriatrics, top 5 in Cardiology/Heart Surgery, and top 20 in Diabetes/Endocrinology, Gastroenterology/GI Surgery, Neurology/Neurosurgery, Orthopedics, Pulmonology/Lung Surgery, Rehabilitation, and Urology. New York Eye and Ear Infirmary of Mount Sinai is ranked No. 12 in Ophthalmology. U.S. News &amp; World Report&rsquo;s &ldquo;Best Children&rsquo;s Hospitals&rdquo; ranks Mount Sinai Kravis Children's Hospital among the country&rsquo;s best in several pediatric specialties. The Icahn School of Medicine at Mount Sinai is ranked No. 11 nationwide in National Institutes of Health funding and in the 99th percentile in research dollars per investigator according to the Association of American Medical Colleges. Newsweek&rsquo;s &ldquo;The World&rsquo;s Best Smart Hospitals&rdquo; ranks The Mount Sinai Hospital as No. 1 in New York and in the top five globally, and Mount Sinai Morningside in the top 20 globally.

Equal Opportunity Employer

The Mount Sinai Health System is an equal opportunity employer, complying with all applicable federal civil rights laws. We do not discriminate, exclude, or treat individuals differently based on race, color, national origin, age, religion, disability, sex, sexual orientation, gender, veteran status, or any other characteristic protected by law. We are deeply committed to fostering an environment where all faculty, staff, students, trainees, patients, visitors, and the communities we serve feel respected and supported. Our goal is to create a healthcare and learning institution that actively works to remove barriers, address challenges, and promote fairness in all aspects of our organization. 
Compensation
The Mount Sinai Health System (MSHS) provides salary ranges that comply with the New York City Law on Salary Transparency in Job Advertisements. The salary range for the role is $132000 - $198065 Annually. Actual salaries depend on a variety of factors, including experience, education, and operational need. The salary range or contractual rate listed does not include bonuses/incentive, differential pay or other forms of compensation or benefits.</div>

Machine Learning Engineer III - Generative AI - Windreich Department of Artificial Intelligence & Human Health Research

Futran Solutions

<div>
 
 
 Title - Machine Learning Engineer Role
 
 
 
 
 Location - New York, NY ( Hybrid 2-3 days onsite)
 
 
 
 
 Face to Face Interview Required
 
 
 
 
 Only W2
 
 
 
 
 
 
 
 Job Description:
 
 
 
 � Analyze large and complex datasets to derive actionable insights and inform business strategies.
 
 
 � Develop and implement advanced machine learning models and algorithms.
 
 
 � Collaborate with cross-functional teams to understand business needs and provide data-driven solutions.
 
 
 � Communicate findings and recommendations to stakeholders and executive leadership.
 
 
 � Stay updated with the latest trends and technologies in data science and machine learning.
 
 
 
 
 
 
 Basic Qualifications:
 
 
 
 � Proficient in Python, Pandas, NumPy, Scikit-Learn, PySpark
 
 
 � Bachelor�s degree in Computer Science, Statistics, Applied Mathematics, or a related field.
 
 
 � Minimum of 8 years of experience in a data science role.
 
 
 � Proficiency in programming languages such as Python or R..
 
 
 � Strong understanding of machine learning techniques and algorithms.
 
 
 
 
 
 
 Preferred Qualifications:
 
 
 
 � Experience with modern ML frameworks such as PyTorch, TensorFlow
 
 
 � Experience with big data technologies such as PySpark
 
 
 � Experience with ML model training within cloud infra such as Azure, AWS, GCP
 
 
 � Proven track record of successfully deploying and optimizing ML models in a production environment.
 
 
 � Excellent communication and visualization skills to effectively present data insights to non-technical stakeholders.
 
 
 
 Thanks &amp; Regards,
 
 
 
 
 Anand Polamarasetti
 
 
 
 
 Recruitment Manager
 
 
 
 
 Panand@futransolutions.com
 
 
 
 
 1235 US Highway 1 STE 2100,
 
 
 
 
 Edison, NJ, 08837, United States
 
 
</div>

Machine Learning Engineer

Software Engineer, AI Native

James Search Group

<div>
 
 
 AI/ML Engineer
 
 
 
 
 Location:
 
 New York, NY
 
 
 
 Compensation:
 
 $135,000 &ndash; $175,000 base + bonus + full benefits, (401(k), and more)
 
 
 
 Industry:
 
 Global P&amp;C Insurance
 
 
 
 
 
 
 About the role and the company.
 
 
 
 James Search Group is working closely with a top-tier global property &amp; casualty insurance carrier to identify an
 
 AI/ML Engineer
 
 to join their enterprise Data and Artificial Intelligence division. This team is driving innovation across the business by developing and scaling AI capabilities that unlock new value and improve decision-making across underwriting, claims, and customer engagement.
 
 
 
 
 
 As an AI/ML Engineer, you'll collaborate with senior team members to build, refine, and deploy predictive models and intelligent systems. The ideal candidate is skilled in analytics, curious by nature, and passionate about transforming complex data into practical solutions that deliver measurable business impact.
 
 
 
 
 
 
 Key Responsibilities:
 
 
 <ul>
 <li>
 Support the development and deployment of AI/ML models&mdash;including classification, forecasting, uplift and propensity modeling, and foundational model tuning.
 </li>
 <li>
 Collaborate with cross-functional teams to identify use cases where data science can enhance operational efficiency and business performance.
 </li>
 <li>
 Partner with business, IT, and strategy teams to ensure AI models are scalable, impactful, and aligned with organizational goals.
 </li>
 <li>
 Communicate analytical findings clearly to stakeholders with varying levels of technical knowledge.
 </li>
 </ul>
 
 
 
 
 
 Required Qualifications:
 
 
 <ul>
 <li>
 Master&rsquo;s degree in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative discipline; Ph.D. a plus.
 </li>
 <li>
 Minimum of 2 years&rsquo; experience applying advanced analytics methods (e.g., decision trees, logistic regression, neural networks, random forests).
 </li>
 <li>
 Proficiency in R or Python for analytics and model development, including work with both structured and unstructured data.
 </li>
 <li>
 Proven ability to manage and integrate large, complex datasets and an understanding of end-to-end data modeling processes.
 </li>
 <li>
 Strong written and verbal communication skills with the ability to connect technical outputs to business strategy.
 </li>
 </ul>
 
 
 
 
 
 Preferred Qualifications:
 
 
 <ul>
 <li>
 Internship or project experience in machine learning, AI engineering, or related roles&mdash;especially in insurance or financial services.
 </li>
 <li>
 Familiarity with actuarial concepts or insurance-specific data models.
 </li>
 <li>
 Enthusiastic about continued learning in AI/ML and staying current with new tools and methodologies.
 </li>
 <li>
 Comfortable in a collaborative, fast-paced, and agile working environment.
 </li>
 </ul>
 
 
 
 
 This is a unique opportunity to grow your career with a highly respected organization investing in next-generation analytics.
 
 
 
 
 
 
 Apply today
 
 to help reshape the future of insurance through data and AI innovation.
 
</div>

QuantumBlack, AI by McKinsey

<div>
 
 Who You'll Work With
 
 
 
 Driving lasting impact and building long-term capabilities with our clients is not easy work. You are the kind of person who thrives in a high performance/high reward culture - doing hard things, picking yourself up when you stumble, and having the resilience to try another way forward.
 
 
 In return for your drive, determination, and curiosity, we'll provide the resources, mentorship, and opportunities you need to become a stronger leader faster than you ever thought possible. Your colleagues&mdash;at all levels&mdash;will invest deeply in your development, just as much as they invest in delivering exceptional results for clients. Every day, you'll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you won&rsquo;t find anywhere else.
 
 
 When you join us, you will have:
 
 
 <ul>
 <li>
 Continuous learning: Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear, actionable, and focused on your development. The real magic happens when you take the input from others to heart and embrace the fast-paced learning experience, owning your journey.
 </li>
 <li>
 A voice that matters: From day one, we value your ideas and contributions. You&rsquo;ll make a tangible impact by offering innovative ideas and practical solutions, all while upholding our unwavering commitment to ethics and integrity. We not only encourage diverse perspectives, but they are critical in driving us toward the best possible outcomes.
 </li>
 <li>
 Global community: With colleagues across 65+ countries and over 100 different nationalities, our firm&rsquo;s diversity fuels creativity and helps us come up with the best solutions for our clients. Plus, you&rsquo;ll have the opportunity to learn from exceptional colleagues with diverse backgrounds and experiences.
 </li>
 <li>
 World-class benefits: On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package to enable holistic well-being for you and your family.
 
 
 </li>
 </ul>
 
 Your Impact
 
 
 
 As a Data Engineer II, you will design, build, and optimize modern data platforms that power advanced analytics and AI solutions.
 
 
 You&rsquo;ll collaborate with clients and interdisciplinary teams to architect scalable pipelines, manage secure and compliant data environments, and unlock the value of complex datasets across industries. You&rsquo;ll sharpen your expertise by working on innovative projects, contributing to R&amp;D, and learning from top-tier talent in a dynamic, global environment.
 
 
 Your work will drive lasting impact. By ensuring data is accurate, accessible, and production-ready, you&rsquo;ll enable clients to accelerate digital transformations, adopt AI responsibly, and achieve measurable business outcomes. Here&rsquo;s how you might contribute in a given year:
 
 
 <ul>
 <li>
 Develop a streaming data platform to integrate telemetry for predictive maintenance in aerospace systems
 </li>
 <li>
 Implement secure data pipelines that reduce time-to-insight for a Fortune 500 utility company
 </li>
 <li>
 Optimize large-scale batch and streaming workflows for a global financial services client, cutting infrastructure costs while improving performance.
 </li>
 <li>
 Develop pipelines for embeddings and vector databases to enable retrieval-augmented generation (RAG) for a global defense client.
 
 
 </li>
 </ul>
 You&rsquo;ll work in cross-functional Agile teams with Data Scientists, Machine Learning Engineers, Designers, and domain experts to deliver high-quality analytics solutions. Partnering closely with clients&mdash;from data owners to C-level executives&mdash;you&rsquo;ll shape data ecosystems that drive innovation and long-term resilience.
 
 
 This role offers an exceptional environment to grow as a technologist and collaborator. You&rsquo;ll develop expertise at the intersection of technology and business by tackling diverse challenges while collaborating with some of the best technical and business talent in the world.
 
 
 There is flexibility to hire at the Engineer I/II or Senior Engineer level, depending on your experience
 
 
 
 Your Qualifications and Skills
 
 
 
 <ul>
 <li>
 Degree in Computer Science, Business Analytics, Engineering, Mathematics, or related field
 </li>
 <li>
 2+ years of professional experience in data engineering, software engineering, or adjacent technical roles
 </li>
 <li>
 Proficiency in Python, Scala, or Java for production-grade pipelines, with strong skills in SQL and PySpark
 </li>
 <li>
 Hands-on experience with cloud platforms such as (AWS, GCP, Azure, Oracle) and modern data storage/warehouse solutions such as Snowflake, BigQuery, Redshift, and Delta Lake
 </li>
 <li>
 Practical experience with Databricks, AWS Glue, and transformation frameworks like dbt, Dataform, or Databricks Asset Bundles
 </li>
 <li>
 Knowledge of distributed systems such as (Spark, Dask, Flink) and streaming platforms (Kafka, Kinesis, Pulsar) for real-time and batch processing
 </li>
 <li>
 Familiarity with workflow orchestration tools such as (Airflow, Dagster, Prefect), CI/CD for data workflows, and infrastructure-as-code (Terraform, CloudFormation)
 </li>
 <li>
 Understanding of DataOps principles including pipeline monitoring, testing, and automation, with exposure to observability tools such as Datadog, Prometheus, and Great Expectations
 </li>
 <li>
 Exposure to ML platforms such as (Databricks, SageMaker, Vertex AI), MLOps best practices, and GenAI toolkits (LangChain, LlamaIndex, Hugging Face)
 </li>
 <li>
 Familiarity with vector databases and understanding of low latency serving patterns is a plus
 </li>
 <li>
 Willingness to travel as required
 </li>
 <li>
 Strong communication, time management, and resilience, with the ability to align technical solutions to business value
 </li>
 </ul>
</div>

Data Engineer II - QuantumBlack, AI by McKinsey

Explore 666+ Machine learning software engineer in New York United States this March. Find roles across top companies and apply now to boost your career.

666 machine learning software engineer jobs In New York United States

Machine Learning Software Engineer

Machine Learning Software Engineer

Machine Learning Engineer III - Generative AI - Windreich Department of Artificial Intelligence & Human Health Research

Machine Learning Engineer

Software Engineer, AI Native

Machine Learning Engineer

Data Engineer II - QuantumBlack, AI by McKinsey