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Softcard (acquired by Google)
Softcard (acquired by Google)
201 – 500 Angajați
Comerț electronicFinanțeFintech
Softcard a fost o platformă de tehnologie financiară și comerț mobil creată de AT&T Mobility, T-Mobile USA și Verizon Wireless. Portofelul său mobil compatibil cu NFC îi ajuta pe consumatori să efectueze plăți contactless, să facă cumpărături de pe telefoanele lor și să acceseze funcții de fidelizare într-un singur loc. Axată pe plăți mobile, portofele digitale și recompense, Softcard a dezvoltat tehnologii concepute pentru a face tranzacțiile de zi cu zi mai rapide și mai personalizate, înainte de a fi achiziționată de Google.
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Locurile de muncă ale companiei

Quantitative Analyst, Portfolio Engineering Analytics

Develop portfolio construction analytics, APIs, forecasting methods, and machine learning models to support investment capabilities at Invesco. Apply quantitative research, optimization, simulation, and data engineering across portfolio and client solutions.

USStatele Unite ale AmericiiMAMassachusettsNYNew York
130.000 $ – 135.000 $ / an
La sediuNormă întreagăNivel mediuSeniorLimbă Obligatorie: englezăAnalist de date
PythonPyTorchScikit-LearnSQLTensorFlow

Descriere

  • Support construction of multi-asset and single-asset portfolios through advanced asset allocation and portfolio construction methods
  • Develop high-performance computing algorithms, infrastructure, and APIs
  • Research and implement prediction and forecasting approaches using statistical methods, machine learning, and Generative AI
  • Convert investment frameworks into practical tools for investment teams and client engagement
  • Apply advanced optimization methods to develop portfolio solutions for internal and external stakeholders
  • Use multi-period simulations to forecast and optimize performance under flows and optionality
  • Incorporate third-party risk models into portfolio construction analyses
  • Create and maintain processes and tools that strengthen data management and research productivity
  • Partner with quantitative and technology teams to apply financial theory and technology best practices
  • Develop research concepts that improve existing frameworks and tools
  • Monitor academic research and industry developments to bring relevant best practices into the work

Cerințe

  • An advanced degree in a quantitative field such as engineering, finance, operations research, or computer science
  • Working knowledge of established financial engineering methods
  • Strong capabilities in statistics and optimization
  • Excellent programming ability, preferably in Python
  • Experience developing and deploying machine learning models in financial applications, especially neural network architectures such as LSTM, CNN, and transformers, is advantageous
  • Proficiency with scikit-learn, TensorFlow, and PyTorch for neural network modeling
  • Experience handling and transforming large datasets, preferably with SQL
  • Ability to learn complex concepts and express them as systematic algorithms
  • Experience with third-party risk models such as BarraOne or Axioma is advantageous
  • Progress toward the CFA designation is preferred
  • Ability to prioritize responsibilities and manage time to maximize impact on the investment process
  • Exceptional attention to detail and a habit of validating and triangulating results
  • Strong interpersonal and collaborative partnership skills
  • Commitment to producing high-quality work

Beneficii

  • Flexible paid time off
  • Hybrid working arrangement
  • 401(k) match equal to 100% of the first 6% contributed, plus a discretionary supplemental contribution
  • Health and well-being programs
  • Parental leave
  • Employee stock purchase plan

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