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Data Science Lead - Applied Innovation

Keywords / Skills : data science, Data Scientist, Python, Cloud, AWS, AZURE, SCALA, tableau

7 - 15 years
Posted: 2019-05-17

Job Description
Our client is a global provider of financial markets data and infrastructure. They equip the financial community with access to an open platform that uncovers opportunity and catalyzes change.

You will be:
  • Creating hypotheses about ways to change the financial industry through new uses of data
  • Building prototypes and MVPs to validate ideas by practically applying data science
  • Working with large, diverse data sets using big data and public cloud technology
  • Defining, organizing and running projects across multiple locations and time zones
  • Translating end user needs to requirements using design thinking methodologies
  • Developing and broadening your skills through mentoring and collaboration with experienced professionals
  • As a part of the company's growing Singapore Lab team of data scientists, engineers and UX/UI designers, you will be part of their global network of like-minded colleagues in their sister labs in London, Singapore, and San Francisco.
Recently the group has worked on graph-based risk analysis, turned text into risk signals, created ML predictions of bond prices, and created real time data simulation. What will you add? The team offers a flexible working environment, values curiosity and supports an open and learning culture for all levels of experience & seniority.

Key Responsibilities:
  • Build minimal viable products utilizing data science techniques directly for our customers
  • Create compelling proposals with technologists and business to drive innovation from conception to production with appropriate success metrics
  • Network in the fintech, big tech and academic community through conferences, meetups and workshops – bringing leading edge techniques and technology into business strategy.
  • Lead projects, removing obstacles and taking ownership to find creative solutions
  • Build domain expertise in financial market content and in the company data and products
Qualifications and Experience Required

Essential Skills:
  • 7+ years industry experience working in a data science role, such as statistics, machine learning, deep learning, quantitative financial analysis, data engineering or natural language processing
  • Experience producing and rapidly delivering minimum viable products, results focused with ability to prioritize the most impactful deliverables
  • Extensive experience using Python or R
  • Proficient in using tools and libraries such as scikit-learn, numpy, pandas and jupyter
  • Positive attitude to learning new skills and technologies
  • Experience with Relational, NoSQL & Graph databases, such as PostgreSQL, MongoDB, Elasticsearch or Neo4J
  • Experience in building and deploying unsupervised, semi-supervised, and supervised models on large datasets
  • Ability to track down complex data quality and data integration issues, evaluate different algorithmic approaches, and analyze data to solve problems. Curiosity about the details of datasets is essential
Desired Skills:
  • Experience using Cloud to perform large scale calculations, such as AWS, Google Cloud Platform or Microsoft Azure
  • Experience with languages frameworks and tools such as Scala, Stan, Spark, Flink, Gremlin and Hadoop
  • Experience with Spark ML/MLLib
  • Experience with deep learning frameworks such as TensorFlow, Keras, Caffe, Torch/PyTorch, Theano, mxnet
  • Experience with graph-based analytics, knowledge graphs
  • Data Visualization with tools such as D3 or Tableau
  • Confidence in communicating complex projects clearly to senior management
  • Domain knowledge in financial services such as quantitative finance, Financial Engineering, Electronic Trading or Risk Modelling
Education / Certifications:
  • Master’s Degree or PhD in a relevant technical field, such as computer science, applied mathematics or a related discipline such as physics or chemistry

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