Staff Scientist, SSP

Position Summary

There are trillions of events a day in our system. That means that whatever models we use must be run at a tremendous scale with milliseconds in latency. We see the success of our models and experiments astonishingly quickly – our learning loop is not measured in weeks or days. It is hours and minutes. We live in what might be the fastest model-learning playgrounds in the world. We have built an infrastructure that enables model deployment at scale and speed. As data scientists, we sit alongside engineering colleagues who enable our models to deploy. Combine this with our growing variable set of hundreds of potential features (and growing!), and this is a highly fertile environment for building, experimenting, refining and achieving real impact from your models. If models fire, the bottom-line impact to our teams is immediate – you see the value of your work incredibly fast.

The Experience You'll Need

• The core foundation we look for is an aptitude with Mathematics, Statistics, Algorithms, Optimization and a competent ability in coding and with data science languages and tools, such as Python or Apache Spark. Most importantly, we look for a passion to investigate and learn about the world from data, to ask interesting and provocative questions, and be driven to put real models into production that drive real business value.
• Basics of big data processing and cloud computing will be critical to succeed in this environment.
• We are open to diverse academic backgrounds, providing an intent to think and problem-solve like a data scientist. Our team includes engineers, mathematicians, computer scientists, statisticians, physicists, economists and social scientists – a rock-star data scientist can come from any academic field. We are looking for a Staff level Data Scientist, but depending on the experience we may hire at a higher or lower level.

Required

• Master’s in a quantitative field such as Computer Science, Statistics, Electrical Engineering, Statistics, Mathematics, Operations Research or Economics, Analytics, Data Science. Ph.D. is a huge plus.
• Depending on the level we are looking for experience in the Ad Tech Industry working in Data Science teams. You would have applied algorithms and techniques from Machine Learning, Statistics, Time Series or other domains in solving real world problems and understand the practical issues of using these algorithms especially on large datasets.
• You are passionate about Mathematics, Algorithms, Machine Learning and eager to learn and apply cutting edge Science to Inmobi business problems. You are excited when you see the real world impact of your models in production. You are fast to execute. You have intellectual depth to translate fuzzy business problems into rigorous mathematical problem statements and algorithms. You have experience and passion in figuring out what to do when ML models don't produce any production lift.
• Comfortable with software programming and statistical platforms such as R, Python etc. Comfortable with the big data ecosystem. Experience in Apache Spark will be a bonus.
• Comfortable collaborating with cross-functional teams.
• Excellent technical and business communication skills and should know how to present technical ideas in a simple manner to business counterparts.
• Possess a high degree of curiosity and ability to rapidly learn new subjects and systems.

The Impact You'll Make

• You will be responsible for leading the data science efforts for one of the biggest in-app programmatic exchange in the world. This involves project ideation and conceptualization, solution design, measurement and solution iteration, coaching, deployment and post deployment management.
• This will also include designing, development, testing of product experiments. You will need to guide the team in practical experiments, product design, model development and model evaluation. It is vital to be agile and iterate fast across experiment to deliver go-to-market ready products.
• You are expected to be a hands-on part of the role where you will also actively analyse data, design and develop models, and problem-solve solutions with the rest of the team.
• Additionally, stakeholder management is needed. It will involve being the interface with internal stakeholders such as our Product, Engineering, Data, Infrastructure, and Business teams.
• Our team strives for thought leadership in the sector. We encourage and support all team members to write blogs, commentary and case studies published on the InMobi blog. We also support team members across our ML/AI team to speak at industry conferences and represent InMobi’s work.
• You will learn how to design and build models for specific business problems. Even before that, you will be responsible for identifying the problem areas where AI can be applied to best business impact. You will learn to start a model design by anchoring in the business context and end user needs. You will learn how to connect model impact with real and measurable business impact.
• You will work in a multi-functional team environment. You will collaborate and benefit from the skills of a diverse group of individuals from teams such as engineering, product, business, campaign management and creative development.
• You will have the opportunity to experiment with multiple algorithms. Enduring learning comes from building, launching and reviewing performance of a particular algorithm; from asking why something worked or why it did not work; from asking how to tailor techniques to fit the problem at hand. We have an environment that makes this possible at speed.
• Importantly, you will learn to become creative in designing models to be successful. Model design is not one-size-fits. Our models need to fit our particular problems and be modified to perform.