Senior Data Scientist

Who we are:

BigID is an innovative tech startup that focuses on solutions for data security, compliance, privacy, and AI data management. We're leading the market in all things data: helping our customers reduce risk, drive business innovation, achieve compliance, build customer trust, make better decisions, and get more value from their data.

We are building a global team passionate about innovation and next-gen technology. BigID has been recognized for:

BigID Named Hot Company in Artificial Intelligence and Machine Learning at the 2024 Global InfoSec Awards
Citizens JMP Cyber 66 List of Hottest Privately Held Cybersecurity Companies
CRN 100 list named BIgID as one of the 20 Coolest Identity Access Management And Data Protection Companies Of 2024 (2 years running)
DUNS 100 Best Tech Companies to Work For in 2024
Top 3 Big Data and AI Vendors to Watch' in the 2023 BigDATAwire Readers and Editors Choice Awards
2024 Inc. 5000 list for the 4th consecutive year!
Shortlisted for the 2024 AI Awards in the category of Best Use of AI in Cybersecurity

At BigID, our team is the foundation of our success. Join a people-centric culture that is fast-paced and rewarding: you'll have the opportunity to work with some of the most talented people in the industry who value innovation, diversity, integrity, and collaboration.

Who we seek:

We're looking for a Senior Data Scientist for the BigID Data Science team. Our Data Science team deals with huge-scale security and privacy-related ML challenges.
As a Senior Data Scientist, you'll be responsible for bringing innovative machine learning algorithms from conception to realization.

What you'll do:

Research and develop state-of-the-art machine learning and neural network algorithms to solve complex privacy and security-related challenges.
Implement the research products of the data science team as scalable production services and machine learning models.
Build products that extract insights out of petabyte-scale databases. These insights help our customers to better control and protect their databases.

What you'll bring:

B.Sc./M.Sc in Computer Science, Mathematics, Statistics, or equivalent.
Highly proficient in Python.
5+ years of proven experience in Machine Learning, Statistical Modelling, and Pattern Recognition.
Proven experience in bringing an ML algorithm from idea to productization.
Experience with open source Machine Learning toolkits: tensorflow, keras, scikit-learn, pandas, numpy.
Team player, willing to work in a dynamic startup environment.
Reliable self-starter capable of working with a high degree of autonomy.

Advantages:

Experience with data engineering - strong advantage.
Experience with LLMs, prompt engineering, agentic workflows - strong advantage.
Experience in document clustering/sentiment analysis/word vectors/embedding - strong advantage.
Experience with NoSQL and BigData - Hadoop/Hive/HBASE, Cassandra, MongoDB, etc. - advantage.
Experience with distributed architecture, microservices, message queues, REST API - advantage.

What's in it for you?!

Our people are the foundation of our success, and we prioritize offering a wide range of benefits that make our team happier and healthier.

Equity participation - everyone shares in our success
Flexible work arrangements - for parents, for remote workdays, etc.
Office perks: dog-friendly environment, fully stocked fridge, gym, and exercise classes, weekly Happy Hours, free parking, evening meals
Knowledge training & Career development tracks

Our Values:

We look for people who embody our values - Care, Do, Try & Shine.

Care - We care about our customers and each other
Do - We do what it takes to make a positive impact
Try- We try our best and we don't give up
Shine- We shine and make it our mission to always stand out

#LI-Hybrid

#LI-AT1

BigDiversity: We're committed to creating a culture of inclusion, diversity, and equality – across race, gender, sexuality, disability, and neurodiversity – where innovation and growth thrive, every voice is heard, and everybody belongs. Learn more about us here.

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