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Senior Data Scientist

QuantumLeap Analytics
San Francisco
Salary Estimate
USD 160.000 – USD 220.000
Latest
Live Update
23 Mei 2026
Deadline
24 Mei 2027

Job Description

Join QuantumLeap Analytics as a Senior Data Scientist and transform complex data into strategic business intelligence. We're seeking a visionary innovator to architect cutting-edge machine learning solutions that drive measurable impact across our fintech portfolio. In this pivotal role, you'll collaborate with cross-functional teams to deliver predictive models, optimize algorithms, and pioneer next-generation analytics platforms. Our culture champions intellectual curiosity, technical excellence, and data-driven decision-making.

Enjoy competitive compensation, comprehensive benefits, and flexible work arrangements in our downtown San Francisco headquarters. We invest heavily in professional development through conference sponsorships, certification reimbursements, and dedicated innovation time. Help us redefine what's possible with data.

Responsibilities

  • Design, develop, and deploy scalable machine learning models for fraud detection, risk assessment, and customer behavior prediction
  • Lead end-to-end data science projects from hypothesis formulation to production implementation
  • Collaborate with engineering teams to integrate ML pipelines into cloud-based data platforms
  • Translate complex findings into actionable business insights for executive stakeholders
  • Mentor junior data scientists and champion best practices in model validation and ethical AI
  • Research and implement novel deep learning architectures for time-series forecasting
  • Optimize data processing workflows using distributed computing frameworks (Spark, Dask)

Qualifications

  • MS/PhD in Statistics, Computer Science, Mathematics, or related quantitative field with 5+ years of industry experience
  • Expert proficiency in Python (scikit-learn, pandas, NumPy) and SQL with database optimization skills
  • Proven track record deploying production ML systems using cloud platforms (AWS/GCP/Azure)
  • Strong statistical foundation in experimental design, hypothesis testing, and causal inference
  • Experience with deep learning frameworks (TensorFlow/PyTorch) and NLP techniques
  • Demonstrated ability to communicate technical concepts to non-technical stakeholders
  • Portfolio showcasing 3+ deployed ML solutions with measurable business impact
  • Experience with A/B testing frameworks and MLOps tooling (MLflow, Kubeflow)

Required Skills

Python SQL Machine Learning TensorFlow PyTorch AWS Statistical Modeling Data Visualization MLOps NLP Distributed Computing

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