Data Scientist - AI & ML Ops
A
AddiFinTech
LatAmFull-TimeMiddle
Salary not disclosed
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Job Details
- Experience
- 3+ years
- Required Skills
- PythonGitPyTorchTensorflowGitHubDeep Learningscikit-learnLLMLangChain
Requirements
- 3+ years of experience building and deploying AI/ML solutions end-to-end.
- Evidence of shipping models with guidance in a collaborative environment, moving beyond local notebooks into production systems.
- Bachelor’s degree in Physics, Mathematics, Statistics, Economics, or Computer Science.
- Demonstrated success in building or contributing to systems that utilize modern LLM approaches (e.g., LangChain, LangGraph).
- Experience designing knowledge bases or retrieval structures to improve the reliability of AI outputs.
- Deep understanding of statistics, experimentation (A/B testing, sampling), and classical ML methods.
- Skilled in neural architectures and optimization, with a working knowledge of attention mechanisms and transformer-based models.
- Proficiency in modern frameworks like PyTorch, TensorFlow, or Scikit-learn.
- Hands-on experience building with LLMs using advanced techniques: prompting, structured outputs, tool use, and guardrails.
- Familiarity with orchestration patterns (routing, memory, handoffs) and retrieval-augmented generation (RAG).
- Mastery of Python for creating reproducible pipelines and evaluation tooling.
- Comfortable working in shared codebases using Git/GitHub.
- Track record of driving efficiency & Impact, prioritizing "Results over Research".
- Exceptional ability to explain the limitations and risks of AI to non-technical stakeholders.
Responsibilities
- Design, build, and operate the Decision Intelligence Engines that power Addi’s personalized customer journeys.
- Transform Addi’s Shop into an automated, AI-driven ecosystem by deploying State-of-the-Art (SOTA) architectures, including Sequential Deep Learning and LLMs to optimize customer LTV, activation, and retention in real-time.
- Design and maintain segmentation models based on behavior, performance, lifecycle stage, and growth potential.
- Design, train, and deploy models to predict customer behaviors and risks, ensuring outputs are interpretable and segment-aware.
- Design and deploy LLM-based solutions for customer growth, treating them as production systems with strong guardrails.
- Develop and Implement ML Models to analyze customer behavior, optimize marketing strategies, and improve overall engagement with Addi’s platform.
- Manage Data Pipelines and Model Deployment in collaboration with data engineering teams.
- Monitor and Evaluate Model Performance, iterate to improve accuracy, scalability, and overall performance.
- Collaborate with product managers, marketing teams, and stakeholders to translate data insights into actionable strategies.
- Innovate by proposing ML models, algorithms, or tools that enhance customer experience and optimize product recommendations.
- Conduct A/B Testing to assess the impact of different offers, product recommendations, and marketing strategies.
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