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.
What’s the InMobi family like?
Consistently featured among the “Great Places to Work” in India since 2017, our culture is our true north, enabling us to think big, solve complex challenges and grow with new opportunities. InMobians are passionate and driven, creative and fun loving, take ownership and are results focused. We invite you to free yourself, dream big and chase your passion.
What do we promise?
We offer an opportunity to have an immediate impact on the company and our products. The work that you shall do will be mission critical for InMobi and will be critical for optimizing tech operations, working with highly capable and ambitious peer groups. At InMobi, you get food for your body, soul, and mind with daily meals, gym, and yoga classes, cutting-edge training and tools, cocktails at drink cart Thursdays and fun at work on Funky Fridays. We even promise to let you bring your kids and pets to work.
What is the team like?
ESG team is responsible for solving business critical challenges by building efficiency/productivity improving tools. ESG is a team of deeply technical individuals with high analytical skills which enables them to handle the ecosystem changes proactively. ESG team is responsible for services like device and app metadata which is essential for smooth functioning of SSP and DSP systems. Reporting platform for media buying unit is another product owned by the team which enables centralised reporting view for audiences ranging from account managers to execs. Along with all these, team also owns and maintains various data pipeline jobs which needs deep expertise on big data technologies.
What will you be doing?
- As Big Data and Data Science Engineer you will develop, maintain, evaluate and test big data solutions. You will be involved in the design of data solutions using Hadoop based technologies like MapReduce, Hive, Spark
- You are responsible for Hadoop development and implementation including loading from disparate data sets, preprocessing using Hive and Pig.
- Scope and deliver solutions with the ability to design solutions independently based on high-level architecture.
- Maintain the production systems like Kafka, Hadoop, Cassandra Elasticsearch
- Analyze large, complex data sets by developing advanced statistical and machine learning models based on business initiatives
- Utilize big data analytics and advanced data mining techniques to direct the gathering of data, assess data validity and synthesize data into large analytics datasets to support project goals
- Build and train scalable models using best practices, enabling re-use for future project
What do we expect from you?
- Exposure/Experience in Big data Technologies such Apache Hadoop, Hive, Spark / PySpark, SQL, Oozie
- Experience writing high quality, maintainable SQL on large datasets.
- Experience in writing code in Java, Python, Scala or other platform-related Big data technology.
- Working knowledge in one NoSQL database like MongoDB/Cassandra/HBase/Couchbase
- Demonstrated ability in solutioning covering data ingestion, data cleansing, ETL, data mart creation and exposing data for consumers
- Expertise in the design, creation and management of large datasets/data models
- Experience with cloud services such as AWS S3, Redshift, EMR or Azure Blob, HDInsight, Databricks etc
- Experience in Statistical Learning: - Predictive & Prescriptive Analytics, Web Analytics, Parametric and Non-parametric models, Regression, Time Series, Dynamic/Causal Model, Statistical Learning, Guided Decisions, Topic Modeling
- Experience in Machine Learning, supervised and unsupervised: - Forecasting, Classification, Data/Text Mining, NLP, Decision Trees, Adaptive Decision Algorithms, Random Forest, Search Algorithms, Neural Networks, Deep Learning Algorithms
- Experience with statistical programming languages, analytical packages/libraries (R, Python) - Experience with statistical tools (R studio, Revolution R, Python notebooks) - Experience with SQL and relational databases, data warehouse platforms (Teradata), NoSQL databases - Experience with big data platforms
- Strong analytical and problem-solving skills
- Excellent verbal and written communication skills
- Ability to work with business owners to define key business requirements and convert to technical specifications
- Proven success in communicating with users, other technical teams to collect requirements, describe data modeling decisions and data engineering strategy
- Data science background and experience manipulating/transforming data, model selection, model training, cross-validation and deployment at scale.
- Experience with Machine and Deep Learning toolkits such as MXNet, TensorFlow, Caffe and Torch.
- Knowledge of software engineering best practices across the development life cycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations