Who are we and What do we do?
InMobi Group’s mission is to power intelligent, mobile-first experiences for enterprises and consumers. Its businesses across advertising, marketing, data and content platforms are shaping consumer experience in a world of connected devices. InMobi Group has been recognized on both the 2018 and 2019 CNBC Disruptor 50 list and as one of Fast Company’s 2018 World’s Most Innovative Companies.
About the team
InMobi Commerce Cloud team is responsible for the retail media products that drive discovery, sales and profits on eCommerce properties.
InMobi Commerce Cloud Group is investing heavily in building a world-class retail media advertising business. We are responsible for defining and delivering a collection of self-service advertising products that drive discovery and sales on eCommerce properties.
Our products are strategically important to our retail media business delivering billions of ad impressions and millions of clicks across top retailer digital media properties. We are highly motivated, collaborative, and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with an endless range of new opportunities.
In InMobi Commerce Cloud, we are applying Machine Learning at a massive scale to optimize retail media advertising performance. We are looking for talented Data Scientists with 3+ years of experience to work on cutting edge machine learning challenges & problems in artificial intelligence for retail media domain. The challenge entails research, prototyping, and experimentation with state-of-the-art ML techniques. You will work together in a team of Data Scientists, Software and Data Engineers, Product Managers and Business Development Leaders.
You will be working on cutting edge retail media advertising use cases such as Bid Price Forecasting, CTR prediction, CTR\CVR optimisation, Ad selection and Campaign performance etc to help increase revenue for advertisers and retailers. You will build the next generation of machine learning models and optimization algorithms that power the real-time smart bidding platform in a fast-paced environment.
You will research the latest advances in ML prediction and forecasting techniques, construct prototypes to validate your hypothesis, work with engineers to turn these prototypes into production systems and perform offline analysis and online A/B experimentation.
You will be encouraged to attend workshops and conferences (internal and external), with opportunities to write papers, participate in science events, and obtain early access to ML technologies from our industry partners.
How will you make an impact?
- Building sophisticated ML models using cutting edge algorithms from a proof of concept to productionised models, monitoring the performance of live models bidding in real-time and producing insight for our advertisers and retailers.
- Develop advanced predictive models, smart bidding systems using reinforcement learning on large-scale datasets using advanced statistical modelling, machine learning and data mining.
- Design and implement scalable models that can work with planet-scale and high-velocity data in production systems
- Your major area of focus will revolve around predictive models, autonomous bidding algorithms, click\conversion optimization, bid price forecasting and reinforcement learning problems
- You will experiment based on your understanding of principles employed in auction theory and game theory
- Continuous research and improvements on productionised models, including ML feature engineering and model training tuning to reflect changes in users’ behaviours and market dynamic.
- Collaborating closely with the product and business leaders to identify, develop and optimise business opportunities.
- Own and execute multiple end to end data science initiatives/projects/product features
- Thought leadership through publishing papers & blogs, presenting in conferences, conducting training sessions, etc.
- Be part of an active group of machine learning practitioners across InMobi Group.
Who you are?
- You have a Master’s \ Post-graduate degree in Computer Science, Machine Learning, Engineering, Mathematics, Physics, or equivalent.
- You have a strong background in machine learning, enjoy applying theory to develop real-world applications, with experience and expertise in machine learning algorithms for autonomous bidder systems/recommender systems and/or computational advertising.
- You have at least 3+ years of work experience in domains such as computational advertising, web search, recommendations, and personalization
- You have hands-on experience implementing production machine learning systems at scale in Python, Scala, Java or similar languages.
- Industry experience with frameworks such as Tensorflow and the Tensorflow ecosystem (TFX) is also a plus.
- You have experience with data pipeline tools like Apache Beam, Spark, etc., and cloud platforms like GCP or AWS.
- Experience handling planet-scale datasets
- Outcome-obsessed, pragmatic scientist who is relentlessly focused on creating positive business impact
- Strong analytical, quantitative problem solving, and communication skills
- You can bridge the gap between research and real world problems, and have great judgement and intuition on which approach will work well in practice
- You excel in communicating complex ML techniques and scientific concepts in an easy-to-understand way
- You are a team player and you thrive in a collaborative environment
- You thrive in a fast-paced environment. You are comfortable getting started with minimal information and can bring clarity via rapid iterations
- Experience working with advertising, retail, financial, or e-commerce data.
- You’re experienced with traditional as well as modern machine learning/statistical techniques, including Regression, Classification, Ensemble Methods, Deep Learning and Reinforcement Learning.
- Experience using Deep Learning, Bandits, Probabilistic Graphical Models, or Reinforcement Learning in real applications
- At least 3+ years of experience in optimizing business metrics through automated algorithms (real-time bidder, recommendation engines, information retrieval, pricing etc.)
- Experience in auction theory, game theory, with a strong background in statistical methodology and/or big data.
- Experience in advanced machine learning topics like Privacy, Fairness, Meta-Learning, Active Learning, Reinforcement Learning, Federated Learning, etc.
- Good understanding in one of the following domains:
- ads bidding & auction
- ads quality control
- online advertising systems (familiar with one or more of these terms: CPC/CPM, CTR/CVR, Ranking /Targeting, Conversion/Budget, Campaign/Creative, Demand/Inventory, DSP/RTB)
- Industry experience in Recommendation Systems, Personalization, Search, Computational Advertising, Natural Language Processing or Computer Vision
- Experience in optimization algorithms and numerical computation