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Lead Data Scientist/ ML Engineer

United States, Philadelphia 80.00 - 90.00 USD / Hour · Job Posted March 26, 2026
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Job Description

This role focuses on building advanced machine learning and AI solutions to better understand customer behavior, pricing dynamics, and sales effectiveness. The position blends deep learning, data science, and generative AI techniques to answer critical business questions such as customer churn, relationship longevity, pricing competitiveness, and sales performance. The role is highly hands‑on and requires ownership of the full lifecycle-from locating and preparing data to developing, evaluating, and deploying models.

Job Responsibility

  • Design, build, and evaluate machine learning models using deep learning, classification, and regression techniques
  • Analyze customer behavior to understand churn drivers, customer lifecycle duration, and relationship development timelines
  • Develop models using historical customer data including order history, pricing trends, and engagement patterns
  • Analyze historical price data to identify pricing behavior, trends, and competitive positioning
  • Build models to assess competitive pricing impacts and identify whether customer loss is driven by price competition
  • Partner with sales leadership to evaluate sales effectiveness, including developing models to assess sales representative performance and knowledge impact
  • Perform end‑to‑end data discovery, sourcing, and preparation across multiple systems and datasets
  • Conduct data mining and exploratory data analysis to uncover patterns and business insights
  • Develop, test, and maintain production‑ready Python code for data science and machine learning workflows
  • Collaborate with business stakeholders to translate analytical findings into actionable recommendations
  • Design and implement prompt engineering strategies for large language models
  • Fine‑tune and adapt LLMs to support business‑specific use cases
  • Build retrieval‑augmented generation (RAG) solutions using vector databases
  • Integrate LLM frameworks and orchestration tools into data science workflows
  • Develop and maintain AI pipelines using frameworks such as LangChain and Semantic Kernel

Requirements

  • Strong background in data science and machine learning
  • Hands‑on experience with deep learning, classification, and regression modeling
  • Advanced Python development experience for data science and ML applications
  • Experience analyzing customer behavior, churn, pricing, or sales performance data
  • Proven ability to independently locate, assess, and prepare complex datasets
  • Experience building models that drive business insights and decision‑making
  • Strong analytical thinking and problem‑solving skills
  • Ability to communicate complex technical findings to non‑technical stakeholders

Nice to have

  • Experience with customer analytics, pricing strategy, or sales performance modeling
  • Experience working with generative AI and LLM‑based solutions
  • Familiarity with vector databases and retrieval‑based AI architectures
  • Experience deploying or operationalizing machine learning models
  • Experience working in fast‑paced, data‑driven environments

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