Principal Data Scientist – Artificial Intelligence, Machine Learning & Big Data
Principal Data Scientist – Artificial Intelligence, Machine Learning & Big Data
Please submit resume to aaron.gao@fmr.com or info@bcicglobal.org
Founded in 1946, Fidelity Investments is one of the world’s largest financial services providers,
with assets under administration exceeding $5.4 trillion, including total managed assets of $2.1
trillion as of December 2016. Fidelity is a premier provider of investment management,
retirement planning, portfolio guidance, brokerage, benefits outsourcing and many other
financial products and services to more than 26 million individual investors and institutional
clients worldwide. Headquartered in Boston, Fidelity currently employs over 45,000
professionals globally on a full or part-time basis across offices in the United States and Canada,
including 170 retail investor centers.
The AIML (Artificial Intelligence and Machine Learning) team contributes to the vitality and
growth of the organization through researching and building complex, cutting edge and scalable
AI algorithms, models, platforms and technologies to significantly improve customer experience
and drive business results. Our team of high caliber scientists, mathematicians and statisticians
use rigorous quantitative approaches to ensure that we are efficiently building algorithms and
technology relevant to the business or customer experience issue at hand. We leverage the
wealth of Fidelity’s data to build a wide range of machine learning / artificial intelligence
models (NLP/NLU, deep learning, reinforcement learning, probabilistic models, clustering
techniques, etc.) and, using Fidelity’s vast infrastructure, we rapidly test, learn and iterate. We
work closely with business stakeholders, collect requirements and deliver high value AI/ML
solutions that drive customer and business value. Those of us who love to work with data see
this as the pinnacle of opportunities that you cannot find anywhere else in the industry.
We are looking for an outstanding Principal Data Scientist who can partner with business
stakeholders, identify/prioritize top AI opportunities, translate business requirements into
technical specifications and transform large volumes of data into ML solutions using creative,
cutting edge, and open source methods/technologies, lead ML strategy and road map planning,
work across teams and influence the direction of external teams. The ideal candidate will
combine expert machine learning/statistics/mathematics knowledge with outstanding
programming skills to manage and deliver complex/critical projects, independently identify and
resolve business/technical issues, and develop best practices.
Responsibilities
You know and love building machine learning algorithms and AI solutions, can build complex
models using massive, heterogeneous and multidimensional datasets and can partner with
stakeholders across a wide range of teams (business, product, technology, etc.). Your
quantitative/programming skills are characterized as one of the best in your organization. You
are analytical, innovative, creative, disruptive, and you don’t give up. In this role, you will have
an opportunity to launch new AI solutions in web, mobile channels, and emerging
platforms/tools (Alexa, Siri, etc.) positively impacting the lives of over 26 million customers.
You will have the opportunity to display your skills in the following areas:
– Interface with business stakeholders, engineers and software developers, gather requirements
and deliver complete AI/ML solutions.
– Own the design, development, and launch of AI solutions that improve customer experience
and deliver business results.
– Closely follow research and open source developments/publications and apply them within
Fidelity’s context.
– Understand, at a deep level, business and product strategies, goals and objectives. Support in
setting the AI roadmap to drive business goals.
BASIC QUALIFICATIONS
PhD (or working towards similar) in Engineering, Computer Science, Mathematics,
Computational Statistics, Operations Research, Machine Learning or related technical fields.
Hands on experience developing supervised and unsupervised machine learning algorithms
(regression, decision trees/random forest, neural networks, feature selection/reduction,
clustering, parameter tuning, etc.), using relevant programming languages (Python,
PySpark, Scala, Java, C++, C#, C, etc.), mathematical/statistical/ML languages and platforms
(R, H2O.ai, Octave, Matlab, Weka, SAS, etc.) and big data tools and languages (Spark,
MapReduce, SQL, Hive, etc.).
Advanced knowledge in model evaluation, tuning and performance, operationalization and
scalability of scientific techniques and establishing decision strategies. Experience in
evaluating and making decisions around the use of new or existing tools for a project.
Proven track record of strong verbal/written communication and presentation skills,
including an ability to effectively communicate with both business and technical teams.
Experience in projects involving large scale-multi dimensional databases, complex business
infrastructure, and cross-functional teams. Three to five successfully launched ML projects.
5+ years of relevant employment experience.
PREFERRED QUALIFICATIONS
Experience with TensorFlow, Keras, Theano, CUDA, and/or DSSTNE.
Experience with advanced ML techniques (RNN, CNN, LSTM, GRU, Genetic Algorithms,
Reinforcement Learning, etc.).
Experience with voice recognition, natural language processing, and computer vision.
Experience building and delivering complex systems that leverage various machine learning
algorithms or technologies that integrate well with other organization-wide systems and
can scale effectively.
Experience in developing and/or launching ML algorithms/frameworks using cloud
infrastructure.
Previous experience in digital-native organizations (Google, Facebook, Amazon, etc.) and/or
the Financial Services industry.