Data Scientist II

About MoEngage

MoEngage is an intelligent customer engagement platform, built for customer-obsessed marketers and product owners. We enable hyper-personalization at scale across multiple channels like mobile push, email, in-app, web push, on-site messages, and SMS. With AI-powered automation and optimization, brands can analyze audience behavior and engage consumers with personalized communication at every touchpoint across their lifecycle.

Fortune 500 brands and Enterprises across 35 countries such as Deutsche Telekom, Samsung, Ally Financial, Vodafone, and McAfee along with internet-first brands such as Flipkart, Ola, OYO, Bigbasket, and Tokopedia use MoEngage to orchestrate their cross-channel campaigns and engage efficiently with their customers sending 50 billion messages to 500 million consumers every month!

Our vision is to build the world’s most trusted customer engagement platform for the mobile-first world.

 We promise to care about your customers as much as you do. And that justifies our top ratings for service and support in Gartner Magic Quadrant, Gartner Peer Insights, and G2 Summer Reports. We have also been recognized as one of the 25 Highest Rated Private Cloud Computing Companies To Work For in a list released by Battery Ventures, a global investment firm based on the employee feedback on Glassdoor where employees reported the highest levels of satisfaction at work during the first six months of the pandemic.

Today, MoEngage is an industry pioneer in the space and engages more than 350M devices. This includes approximately 250B events tracked per month, 30B+ messages sent, to millions of users across the globe.

As part of the Data Science/Engineering team at MoEngage, here are some things you can expect:

•  Take ownership and be responsible for what you build - no micromanagement
•  Work with A players (some of the best talents in the country), and expedite your learning curve and career growth
•  Make in India and build for the world at the scale of 900 Million active users, which no other internet company in the country has seen
•  Learn together from different teams on how they scale to millions of users and billions of messages.
•  Explore the latest in topics like Data Pipeline, MongoDB, ElasticSearch, Kafka, Spark, Samza and share with the team and more importantly, have fun while you work on scaling MoEngage.

• Understand product requirements and execute end-to-end data product pipelines, including research, scoping, data analysis, modeling, prediction, testing, and documentation.
• Translate product requirements into code logic with minimal guidance.
• Take ownership of a module of data science logic and ensure its successful delivery.
• Build quick proof of concepts (POCs) to validate hypotheses
• Collaborate with Product Offerings and Data Engineers/Technical teams to validate and implement product features.
• Handle large data sets, perform statistical analysis, and present insights and findings in a clear and concise manner.
• Proficient in using data visualization tools such as Tableau, Seaborn or Matplotlib to present insights and findings to stakeholders.
• Own, build, deploy, and maintain a scalable machine learning system with the support of the team.
• Manage the entire machine learning product development cycle from ideation to deployment.
• Identify opportunities for feature-level improvements and recommend changes to enhance solution performance.
• Actively participate in the implementation of new frameworks or concepts within data science modules to improve efficiency and effectiveness.
• Mentor and support new team members to facilitate their growth and development.

• Must have 3-5 years of relevant experience.
• Strong working knowledge of Python/Java
• Understanding of ML concepts - probabilistic methods, supervised and unsupervised learning algorithms.
• Strong engineering and coding skills.
• Experience with working on public cloud systems like AWS/Azure/GCP
• Experience of applying ML, statistics, programming and advanced mathematics to build intelligent systems.
• Experience with Recommendation systems and reinforcement learning is a plus

• Work at Scale and challenge yourself.
• Work with a smart team which grew up in the Mobile First world.
• Opportunities for professional growth and advancement.
• Collaborative and inclusive work environment.
• Access to cutting-edge tools, technologies, and data sets.
• Opportunity to work in a fast-paced and innovative industry.