Sr. Data Scientist

1. About Our Client:

The organization operates in the B2B technology sector, focusing on enhancing revenue growth and efficiency for businesses through advanced AI, big data, and predictive analytics. It addresses the challenge of identifying buying intent and engaging targeted accounts to convert pipelines into revenue. The company leverages cutting-edge technology to support revenue teams in driving business growth.

2. About the Opportunity:

The Sr. Data Scientist role is centered on developing and deploying scalable machine learning and AI systems that directly impact product innovation and customer outcomes. This position contributes by transforming advanced AI research into production-grade applications, including NLP, large language models, and agentic AI workflows, thereby advancing the organization''s AI capabilities and product offerings.

3. Responsibilities:

• • Design, build, and deploy scalable machine learning and AI solutions in production.
• • Develop NLP and transformer-based systems for enterprise applications.
• • Build agentic AI workflows using frameworks like LangGraph and LangChain.
• • Manage the end-to-end machine learning lifecycle: data exploration, feature engineering, model development, evaluation, deployment, and monitoring.
• • Develop ranking, recommendation, classification, prediction, and optimization models.
• • Collaborate with Product, Engineering, and Analytics teams to address complex business problems.
• • Enhance performance, scalability, reliability, and observability of production ML systems.
• • Contribute to AI platform architecture and technical strategy.
• • Mentor engineers to promote engineering excellence across the organization.

### 4. Requirements:

• • Minimum of 8 years experience in building and deploying machine learning solutions in production.
• • Strong foundation in machine learning, statistics, and applied data science.
• • Expertise in supervised and unsupervised learning, recommendation systems, ranking models, and predictive modeling.
• • Deep knowledge of NLP, transformers, embeddings, encoder-decoder architectures, and retrieval-based systems.
• • Practical experience with GenAI ecosystems such as LangGraph, LangChain, and Amazon Bedrock.
• • Proficiency in Python programming.
• • Experience with distributed ML systems and pipelines using AWS and Databricks.
• • Strong understanding of feature engineering, model evaluation, and MLOps.
• • Ability to independently resolve ambiguous problems and drive execution.
• • Product-oriented mindset focused on customer impact and business results.
• • Preferred: Experience with agentic AI, multi-agent systems, RAG architectures, vector databases, prompt engineering, PyTorch and/or TensorFlow, and B2B SaaS or customer-facing AI products.

5. Pay Range and Compensation Package:

• • Base salary range: $162,923.67 to $238,954.71, subject to factors including location and experience.
• • Additional compensation may include bonuses, commission plans, and stock options pending board approval.

6. Benefits & Perks:

• • Health insurance coverage.
• • Life and disability insurance.
• • 401(k) employer matching program.
• • Paid holidays, paid parental leave, and paid time off.
• • Quarterly self-care days.
• • Stock options.
• • Learning and development initiatives including access to LinkedIn Learning.
• • Wellness education sessions and employee resource group events.

Equal Opportunity Statement: Our client is an equal opportunity employer. They celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, or national origin.

Note:

RemoteHunter is not the Employer of Record (EOR) for this role. Our purpose in this opportunity is to connect exceptional candidates with leading employers. We help job seekers worldwide discover roles that match their goals and guide them to complete their full application directly through the hiring company’s career page or ATS.