Lead Data Scientist
Freshworks provides innovative customer engagement software for businesses of all sizes, making it easy for teams to acquire, close, and keep their customers for life. Freshworks Software-as-a-Service (SaaS) products provide a 360-degree view of the customer, are ready to go, easy to use, and offer a quick return on investment. Headquartered in San Mateo, USA, Freshworks 2,000+ team members work in offices throughout the world. Freshworks has global offices in India, Singapore, Australia, UK, Netherlands, France, and Germany. The company counts over 220,000 businesses in its customer-for-life community around the world including Honda, Bridgestone, Hugo Boss, University of Pennsylvania, Toshiba, Sling TV, and Cisco.
Freshworks’ suite of products that transform the way world-class organizations collaborate with customers and co-workers include Freshdesk (Omni-channel customer support), Freshservice (IT Service Desk), Freshsales (Intuitive fully-integrated CRM… Freshmarketer (Marketing Automation Suite), Freshteam (HR Management System for growing teams), Freshchat (Modern messaging software) and Freshcaller (Cloud PBX system).
Freshworks has received numerous accolades from analysts and media including making it to Forbes’ Cloud 100 list, Economic Times Startup of the Year, 2019 LinkedIn Top 25 Companies to work for in India and a listing on the Magic Quadrant for CRM Customer Engagement & IT Service Management. While Freshworks has had incredible organic growth over the last few years, the company also has made targeted acquisitions that add critical capabilities to the portfolio including Natural Language Processing, Chatbots, Machine Learning, Social and Messaging Transformation. Freshworks has raised over $400 million in the capital and is funded by Accel, CapitalG, Sequoia Capital and Tiger Global Management. More information is available at www.Freshworks.com.
About the role:
The application of DS/ML in customer engagement like ours is a green field with many new problems to solve like how to enable customer retention, reduce customer churn, understand customer emotion and hence predic buyer behaviour. Freshworks also offer diverse kinds of data. For eg. Several millions of minutes of audio data is available for our freshcaller caller product. We have data on both voice and texts. Someone who is interested in the NLP space will be super excited by the enormous repository of data on e-mails, chat, website visits, social network messages of the companies available. We also work on the events space (website visits, webinar, app based events). More the data more is the scope for DS/ML making it all the more interesting. As an AI/ML engineer you will focus on building next-generation platform services to enable Machine learning capabilities across the Freshworks suite of products. As part of your job, you will extensively use your knowledge of distributed systems and scalable, high-performance systems to build ML pipelines and API services.
• Collaborate with product and business teams to understand all aspects of the problem
• Define the right target metrics that best represent the end-user value
• Apply knowledge of ML, statistics, and advanced mathematics to conceptualize, experiment and design an intelligent system
• Build efficient systems for processing large amounts of data; be proficient with distributed programming frameworks such as Hadoop/Spark
• Solid background in at least two of the following areas: Natural language processing, statistical ML techniques, graph algorithms, constraint optimization, signal processing (speech or vision), deep learning, distributed systems
• Work closely with Data Scientists and come up with scalable system and model architectures for enabling real-time ML/AI services
• Build ML pipelines end-to-end, including stages such as data pre-processing, model generation, cross-validation, and share feedback
• A Bachelor’s degree or a higher degree in Computer Science, Statistics, Mathematics, or a related field.
• Strong problem-solving and programming skills
• Solid understanding of mathematical underpinnings behind Machine Learning algorithms and proficiency in probability, statistics, linear algebra, calculus, and optimization.
• Must have experience in ML with a proven record of successful ML projects with strong individual contribution
• Experience with NLP, Distributed Systems, large scale computing, Big Data technologies like Hadoop and Spark are plus.
• Solid background in at least two of the following areas: Natural language processing, statistical ML techniques, graph algorithms, constraint optimization, signal processing (speech or vision), deep learning, distributed systems.
• Proficiency with Database systems, schema design (SQL and noSQL)
• Must have solid Experience on any of these tools – CNN, LSTM, Resnet