Applied Scientist IV

IntePros; United States; Remote; USD 140,000 - 375,000; Full time

Job summary

A leading technology company seeks an Applied Scientist to innovate AI solutions focused on deep learning and predictive modeling. The successful candidate will enhance user experiences through personalized algorithms, design predictive models for customer acquisition, and collaborate on advanced machine learning projects in a dynamic team environment.

Qualifications

• 6+ years of applied research experience (or 4+ with PhD).
• Hands-on experience building and deploying production-grade ML models.
• Strong proficiency in statistical analysis and big data.

Responsibilities

• Develop deep learning algorithms for personalization.
• Implement predictive lead scoring models.
• Architect ML pipelines and conduct A/B testing.

Skills

Applied Science

Deep Learning

Recommender Systems

Transformers

Multi-Objective Tasks

Education

PhD in relevant field

Tools

Python

PyTorch

SQL

Spark

SageMaker

Job description

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We are seeking an Applied Scientist with a strong background in deep learning, personalization, and predictive modeling. This role will focus on designing and deploying machine learning models that drive customer segmentation, adaptive recommendations, and lead prioritization to optimize business outcomes.

Key Responsibilities

• Develop deep learning-driven personalization algorithms to enhance user experiences across multiple channels (e.g., website, email, etc.).
• Design and implement predictive lead scoring models to optimize customer acquisition, conversion, and retention strategies using advanced techniques like survival analysis, graph networks, or transformer-based architectures.
• Architect end-to-end machine learning pipelines, including data preprocessing, distributed training, model optimization, and real-time inference.
• Research and innovate in multi-modal modeling (text, graph, behavioral, and temporal data) to enhance personalization and lead scoring accuracy.
• Conduct rigorous A/B testing, causal inference, and counterfactual analysis to measure model impact and drive iteration.
• Collaborate with MLOps engineers to streamline model deployment, monitoring, and retraining using tools like SageMaker, MLflow, or other internal frameworks.
• Participate in science reviews to raise the technical and research standards within the organization.
  
  

Top 3 Must-Have Skills:

• Applied Science
• Deep Learning
• Experience with Recommender Systems, Transformers, or Multi-Objective Tasks
  
  

Skills & Experience Required:

• 6+ years of applied research experience (or 4+ years with a PhD)
• 3+ years of hands-on experience building, deploying, and monitoring production-grade machine learning models
• Strong proficiency in Python and PyTorch
• Real-world experience in recommender systems, transformers, or multi-objective modeling
• Extensive knowledge in a breadth of machine learning topics
• Strong background in statistical analysis, experimental design, and working with big data using SQL/Spark
• Ability to simplify complex technical concepts for stakeholders
  
  

Preferred Qualifications:

• Experience deploying deep learning models, such as BERT/Transformers for NLP, diffusion models, GANs, or general DNNs, to solve business problems
• Experience working at organizations operating at large scale
• Publications or patents in applied ML domains
• Expertise in at least one area from each of the following categories:
• MLOps: CI/CD pipelines, model monitoring, cloud platforms, and deployment strategies
• Emerging Techniques: LLM fine-tuning, federated learning, automated feature engineering, siamese networks, efficient transformer architectures
• Experience in at least one of the following areas:
• Personalization: Session-based and long-term interest recommendations, Two-Tower and Transformer-based architectures
• Lead Scoring / Behavioral Modeling: Predictive analytics, churn modeling, and causal ML for attribution
  

This role provides an exciting opportunity to work on cutting-edge AI solutions that drive customer engagement, leveraging state-of-the-art modeling techniques to influence real-world business decisions.

Remote

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Research, Analyst, and Information Technology

• Industries

  IT Services and IT Consulting

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