Remote Data Scientist - B2B SaaS - Greenfield

Remote Full-time
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Job details...
Fully remote Lead Scientist - B2B Saas
This Jobot Job is hosted by Jesse Gray
Are you a fit? Easy Apply now by clicking the "Easy Apply" button and sending us your resume.
Salary $160,000 - $200,000 per year
A Bit About Us
Job Details
We are seeking a highly motivated and experienced Data Scientist to join our dynamic team. This is a permanent, fully remote position, offering you the flexibility to work from anywhere. This role is perfect for someone who thrives in a fast-paced, high-growth environment and is eager to apply their expertise in data science to solve complex business problems in the B2B SaaS sector. The successful candidate will have the opportunity to work on a greenfield project within the technology industry, leveraging AI and machine learning to create innovative solutions that will drive our business forward.
Why join us?
Responsibilities
• Leverage your expertise in Natural Language Processing (NLP), computer vision, and machine learning to develop and implement models that will drive strategic decision-making.
• Collaborate with cross-functional teams to identify opportunities for leveraging company data to drive business solutions.
• Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting, and other business outcomes.
• Develop company A/B testing framework and test model quality.
• Develop processes and tools to monitor and analyze model performance and data accuracy.
• Stay updated with latest technology trends and apply your knowledge to introduce new technologies that can benefit the company.
• Coordinate with different functional teams to implement models and monitor outcomes.
• Develop and maintain robust data processing pipelines, databases, and APIs to support the company's product needs.
Job Details
Qualifications
• A minimum of 3 years of experience in data science or related field.
• Strong problem-solving skills with an emphasis on product development.
• Experience using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets.
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Experience with distributed data/computing tools Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
• Experience with cloud services (Azure, Google Cloud, AWS) and understanding of distributed computing principles.
• Proficiency in using query languages such as SQL, Hive, Pig.
• Experience with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn).
• Excellent written and verbal communication skills for coordinating across teams.
• A drive to learn and master new technologies and techniques.
• Experience in marketing or ad marketing is a plus.
• Advanced degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.
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