Lead Data Scientist

Company Description

About Freshworks

Freshworks makes it fast and easy for businesses to delight their customers and employees. We do this by taking a fresh approach to building and delivering software that is affordable, quick to implement, and designed for the end user. More than 50,000 companies -- from startups to public companies -- around the world use Freshworks software-as-a-service to enable a better customer experience ]CRM) and employee experience (ITSM, HRSM). Headquartered in San Mateo, California, Freshworks has a dedicated team operating from 13 global locations to serve 50,000+ customers including Bridgestone, Chargebee, DeliveryHero, ITV, Klarna, Multichoice, OfficeMax, TaylorMade and Vice Media.

Freshworks transforms the way world-class organizations collaborate with customers and co-workers. The suite includes Freshdesk (omni-channel customer support), Freshsales (sales automation), Freshmarketer (marketing automation), Freshservice (IT service desk), Freshteam (HR management system). Freshworks has received numerous accolades including 2019 Startup of the Year form Economic Times, #16 ranking on the Forbes’ Cloud 100 list and #22 on the Battery Ventures/Glassdoor Best Places to Work in 2020. Our suite of products has also been recognized by analysts including the Gartner Magic Quadrants for CRM Customer Engagement, IT Service Management and Sales Force Automation.

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 capital and is funded by Accel, CapitalG, Sequoia Capital and Tiger Global Management. More information is available at www.Freshworks.com.

At Freshworks, we are creating a global workplace that enables everyone to find their true potential, purpose and passion, irrespective of their background, gender, race, sexual orientation, religion or ethnicity. We are committed to providing equal opportunity for all and believe that diversity in the workplace creates a more vibrant, richer work environment that advances the goals of our employees, our communities and our business.

Job Description

What is Observability platform:

Observability platform service provides deep visibility into modern distributed systems for faster, automated problem identification and resolution. As an on the Observability team, you will be part of a new service called ML Observability and you will be leading the initiatives on the driving solutions on the business problems we have. If you are the kind of data scientist who is passionate about building ML models on huge data sizes in the scale of Petabytes of logs data getting ingested per week or billions of samples per day, this will interest you.

Responsibilities:

ML Observability will be a new offering from Observability foundation service as we have huge data patterns residing in the system. ML Observability will be used to monitor, troubleshoot, and explain machine learning models as they move from research to production environments. An effective observability tool should not only automatically surface issues, but drill down to correlating alerts among different services, identifying the root cause of your problem through anomaly detection and act as a guardrail for models in production. You will be also working on supporting semantic search abilities, forecasting traffic trends and many more data driven business use cases.

• Apply knowledge of ML, statistics, and advanced mathematics to conceptualize, experiment and design an intelligent system to augment the existing Observability system.

• Solid background in the following areas: Natural language processing, NLP for Semantic Search support and distributed systems 

•  Work closely with the backend engineers and come up with scalable system and model architectures for enabling real-time ML services

• Build ML pipelines end-to-end, including stages such as data pre-processing, model generation, cross-validation, and retrain based on feedback. 

• Gathering & analyzing data, devising data science solutions for high-performance models in scalable code. Propose innovative algorithms and pursue patents where appropriate.

• Collaborate with product and business teams to understand all aspects of the problem

 Minimum Requirements:

• A Bachelor’s degree or a higher degree in Computer Science, Statistics, Mathematics, or a related field.

• Have basic experience in Machine Learning/AI techniques including Deep learning (RNN, CNN, GAN, etc), Support Vector Machines; Regularization Techniques; Boosting, Random Forests, Ensemble Methods, Bayesian and time series modeling, NLP.

• Have good experience with Python, SQL.

• 5+ years of experience in data science

Preferred Requirements:

• Experience with time series analysis, NLP, Distributed Systems, large scale computing, Big Data technologies like Hadoop and Spark.

• Have experience in Parallel programming frameworks for GPUs, TPUs and developed containerized solutions (Docker/Mesos etc).

• Have good implementation experience with R, Python, Perl, Ruby, Scala, Apache Spark, Storm, SAS and ability to work with a variety of Deep learning frameworks including TensorFlow, Keras, Caffe, CNTK, etc.

• Good understanding of object oriented programming.

• Must have solid Experience on any of these tools - CNN, LSTM, Resnet 

• 5 years of experience in data science.

Additional Information

All your information will be kept confidential according to EEO guidelines.

At Freshworks, we are creating a global workplace that enables everyone to find their true potential, purpose, and passion irrespective of their background, gender, race, sexual orientation, religion and ethnicity. We are committed to providing equal opportunity for all and believe that diversity in the workplace creates a more vibrant, richer work environment that advances the goals of our employees, communities and the business.