7+
Experience
Full Time
Job Type
B2
English Level
Who We’re Looking For
We are looking for a smart, talented and self-motivated Senior Data Scientist to join our growing family.
What You’ll Do
ML Architecture & Development (80%)
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Zero-to-One Development: Design and implement the foundational ML architecture for Maverick’s predictive modules.
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Financial Forecasting: Build robust time-series and predictive models for Accounts Receivable/Accounts Payable forecasting and cash flow optimization.
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Anomaly Detection: Develop algorithms to identify outliers, fraudulent transactions, or irregular financial patterns (leveraging approaches like Autoencoders, GMMs, or Isolation Forests).
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Model Training & Evaluation: Train, evaluate, and tune various models using Scikit-Learn, XGBoost, LightGBM, TensorFlow, or PyTorch.
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Advanced ML Techniques: Explore and implement state-of-the-art approaches, including Graph Attention Networks or Reinforcement Learning, for complex financial recommendations and optimization tasks.
Collaboration & MLOps Integration (20%)
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Architectural Alignment: Work closely with the Principal Architect to align ML models with business goals and the overall system architecture.
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Data Pipeline Collaboration: Partner with Data Engineers to ensure clean, reliable data feeds from Snowflake, utilizing dbt and Airflow.
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Production Deployment: Collaborate with MLOps to deploy models securely on AWS (e.g., using Amazon SageMaker).
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Cross-Functional Synergy: Work with the AI Engineering team to integrate predictive ML outputs with LLM-powered agentic workflows (LangGraph).
What You’ll Need
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Programming: Python 3.x (advanced proficiency).
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ML/Data Science Libraries: Pandas, Numpy, Scikit-Learn, XGBoost, LightGBM, Ray Framework
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Deep Learning: PyTorch
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Data Handling: Advanced SQL, experience with data warehouses (Snowflake, BigQuery, or Redshift).
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Cloud & MLOps: Docker, k8s, Cloud AI Platforms (Amazon Sagemaker/Bedrock, GCP AI Hub, Azure AI/Machine Learning/Cognitive Services), Ray Cluster, MLFlow, Jupyter Hub/Lab
Nice to Have:
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Advanced ML Concepts: Experience with Graph Neural Networks (GNNs), Reinforcement Learning, or Nupic HTM.
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Data Engineering Tools: Apache Spark, Airflow, dbt.
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LLM Ecosystem: Basic understanding of LangChain, LangGraph, or HuggingFace to speak the same language as our AI engineers.
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API Frameworks: FastAPI or Flask for model serving.
Technical Skills
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5-7+ years of hands-on experience in Data Science or Machine Learning Engineering.
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Proven track record of building ML modules from scratch and taking them to production.
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Deep mathematical and statistical understanding of algorithms (you don’t just use .fit(), you understand the math behind the models).
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Experience with anomaly detection, demand prediction, and time-series forecasting.
Professional Skills
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Excellent English communication (written and spoken).
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Extreme Ownership: Ability to operate independently in a “greenfield” environment.
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Collaborative: Comfortable working alongside a highly technical Principal Architect and taking high-level direction to execute tactical implementations.
Preferred Qualifications
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Background in FinTech, corporate finance, or e-commerce.
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Experience with programmatic marketing optimization (e.g., automated discount construction, inventory optimization).
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Familiarity with multi-tenant SaaS architectures.
What We Offer
- Competitive salary
- Remote work opportunity
- Comfortable work in your local time zone
- Flexible work schedule
- Professional growth and development
- Multicultural working environment
