Are you passionate about collaborating around technical data challenges to creatively solve complex problems? Come join us!
Our company provides a unique opportunity to work in a global company with a huge amount of high-quality data.
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
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? Our team offers a flexible working environment, values curiosity and supports an open and learning culture for all levels of experience & seniority.
- 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
- Lead and inspire an extremely talented team of data scientists and sr. data scientists while actively contributing to projects and a manager
- Lead all projects from a data science perspective, removing obstacles and taking ownership to find creative solutions
- Manage senior level stakeholder engagements internally and externally to discover problems and use cases as well as to translate business impact of on-going and completed projects.
- Build domain expertise in financial market content and in data and products
- Network in the fintech, big tech and academic community through conferences, meetups and workshops - bringing leading edge techniques and technology into business strategy.
- 10+ years industry experience working in a data science role, such as statistics, machine learning, deep learning, quantitative financial analysis or natural language processing.
- Proven track record leading and contributing to data science teams, conveying objectives and expectations with clarity to align to business goals involving an inclusive, knowledge sharing and feedback oriented culture to nurture talent
- Experience producing and rapidly delivering minimum viable products, results focused with ability to prioritize the most impactful deliverables.
- Stellar interpersonal skills with a result-oriented attitude and a proven ability to handle multiple complex projects in a dynamic and collaborative group settings.
- High level of confidence in communicating with senior business and technical leaders internally and externally
- 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 working with large datasets to build unsupervised, semi-supervised and supervised for both machine learning and deep learning models
- Experience in at least several of the algorithm techniques i.e. Clustering, Classification, Regression, Decision Trees, Neural Networks, Random Forest, Support Vector Machines, Hidden Markov Models, Latent Dirichlet Allocation, etc.
- 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
- Domain knowledge in financial services such as quantitative finance, Financial Engineering, Electronic Trading or Risk Modelling.
- 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 in handling large and distributed datasets on Spark, Hadoop, Hive, Pig or Storm, etc.
- Experience in machine learning/deep learning pipelines, data ingestion, feature engineering and selection, model training, validation and deploying large-scale machine learning/deep learning models in the cloud environment
Education / Certifications
- Preferred: 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
For more information about this role please contact our Singapore office Spencer Ogden Energy Pte Ltd Agency License Number: 13C6321