Applied Scientist Ii

**Applied Scientist II**:
Bangalore, Karnataka, India

Date posted

**Jun 01, 2025**
- Job number

**1827424**
- Work site

**Up to 50% work from home**
- Travel

**0-25**%**
- Role type

**Individual Contributor**
- Profession

**Research, Applied, & Data Sciences**
- Discipline

**Applied Sciences**
- Employment type

**Full-Time**

**Overview**:
We are a team of applied scientists working on machine learning components in the whole sponsored search stack. Our team works on problems related to machine learning, deep learning, natural language processing, image understanding, optimization, information retrieval, among others. Our work entails building large-scale machine learning systems for user response modelling, ranking, and a number of other ML-driven business problems. The **Applied Scientist II** will design, implement, analyze, tune complex algorithms and ML systems and the supporting infrastructure for operating on large datasets. They will collaborate with top machine learning scientists and engineers in delivering direct business impact. We're looking for sound understanding and insight into productionizing machine learning models in large-scale systems, an ability to pick up new technical areas, as well as a commitment to developing, delivering, and supporting algorithms in production

Microsoft’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.

**Qualifications**:
**Required Qualifications**:

- 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.
- Solid understanding of probability, statistics, machine learning, data science, A/B testing & analysis of ML models, and optimizing models for accuracy.
- Experience with end-to-end system design: data analysis, feature engineering, technique selection & implementation, debugging, and maintenance in production.

**Other Requirements**:
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.

**Preferred Qualifications**:

- Experience with Hadoop, Spark, or other distributed computing systems for large-scale training & prediction with ML models.
- Experience implementing machine learning algorithms or research papers from scratch.
- Experience with TensorFlow/PyTorch and deep learning models.

MicrosoftAI

**Responsibilities**:

- Design and develop large scale online and offline platform tools for Ads related products.
- Develop novel algorithms in the space of sponsored search to constantly improve the operational efficacy and monetization impact to stake holders.
- Analyze Giga/Tera bytes of logs and create observation/opportunities and avenues of improvements in the system.
- Ideate on newer aspects of advertising avenues and augment the platform with richer products for the stake holders.
- Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.
- 

Industry leading healthcare
- 

Educational resources
- 

Discounts on products and services
- 

Savings and investments
- 

Maternity and paternity leave
- 

Generous time away
- 

Giving programs
- 

Opportunities to network and connect