Lead Data Scientist
Birdeye
description
Why Birdeye?
Birdeye is the highest-rated reputation, social media, and customer experience platform for local businesses and brands. Over 150,000 businesses use Birdeye’s AI-powered platform to effortlessly manage online reputation, connect with prospects through social media and digital channels, and gain customer experience insights to grow sales and thrive.
At Birdeye, innovation isn't just a goal – it's our driving force. Our commitment to pushing boundaries and redefining industry standards has earned us accolades as one of the foremost providers of AI, Reputation Management, Social Media, and Customer Experience software by G2.
Founded in 2012 and headquartered in Palo Alto, Birdeye is led by a team of industry experts and innovators from Google, Amazon, Salesforce, and Yahoo. Birdeye is backed by the who’s who of Silicon Valley - Salesforce founder Marc Benioff, Yahoo co-founder Jerry Yang, Trinity Ventures, World Innovation Lab, and Accel-KKR.
Role Description: This is a full-time remote role for a Data Scientist at Bideye.
Primary Skills: Data Science, AI/ML, GenAI, LLM, NLP, Any Cloud (Azure/AWS/GCP)
Roles & Responsibilities:
- Develop custom data models and algorithms to apply to data sets.
- Developing and implementing advanced machine learning models to address complex problems.
- Clearly communicate findings and recommendations, data-driven insights to PMs and executives.
- Develop custom data models and algorithms to apply to data sets.
- Developing and implementing advanced machine learning models to address complex problems.
- Lead and mentor a team of data scientists, providing guidance on best practices and technical expertise.
- Collaborate with cross-functional teams to define data-driven strategies and integrate data science solutions into products.
- Continuously evaluate and improve the performance of existing models and algorithms.
- Stay updated with the latest advancements in AI/ML and propose innovative solutions to enhance the company's capabilities.
requirements
- Bachelors/Masters degree in Computer Science, Engineering, or a related technical field with minimum 5-8 years' experience.
- Minimum of 2 years of experience in leading a team of junior Data Scientist.
- Should have been involved in end-to-end delivery of the scalable, optimized and enterprise AI solutions.
- Experience in performing prompt engineering and fine-tuning of the AI/ML, GenAI, LLM models.
- Practical hands-on fine-tuning/transfer learning/optimization of the Transformer architecture based Deep Learning models.
- Experience in NLP tools such as Word2Vec, TextBlob, NLTK, SpaCy, Gensim, CoreNLP, BERT, GloVe etc.
- Experience in AWS / Azure / GCP cloud and deploying the APIs using the latest frameworks like FastAPI/ gRPC etc.
- Experience in Docker for deploying the containers. Deployment of the ML models on the Kubernetes clusters
- Experience in NoSQL/SQL databases.
- Good programming skills in Python.
- Domain knowledge in Online Reputation management or experience in a product-based company (added advantage).
- Expertise in delivering end-to-end analytical solutions covering multiple technologies & tools to multiple business problems.
- Understanding of big data technologies like Hadoop, Spark, and Hive.
- Strong knowledge of statistical methods and experimental design.
- Experience with MLOps practices for CI/CD in machine learning.
- Strong project management skills, with the ability to manage multiple projects simultaneously.
- Excellent communication and presentation skills, with the ability to explain complex technical concepts to non-technical stakeholders.
Why You’ll Join Us
At Birdeye, we are relentless innovators driven by a singular goal: to lead our category with unparalleled excellence. We don't just set goals – we surpass them. We're a team of doers who roll up our sleeves and get the job done, delivering on our promises with unwavering dedication.
Working here means embracing a culture of action and accountability, where every person is empowered to make an impact. We don't just talk about making a difference – we make it happen.