Director, Data Science - 2044481
Company: Fidelity Investments
Location: Boston, MA
Posted on: January 28, 2022
Job Description:
Builds ML models that are supervised and unsupervised and
engages in reinforcement learning in a large financial services
environment. Analyzes and evaluates Machine or Deep Learning (ML
and DL) models in online advertising (clickstream data, Adobe, and
Google Analytics), recommender systems (Bayesian models,
collaborative systems, restrictive boltzman machines, and
reinforcement learning), and user behavior applications (neural
network classifiers and RNNs), using R, Python, or C++. Develops
and leads ML approaches for multiple concurrently projects with
diverse scope and complex business and technical challenges across
several business units and functions. Manages end-to-end data
science and ML projects, using project management methodologies
(Agile, Scrum, or Kanban) and technologies (Atlassian Stack). Draws
on in-depth knowledge of the business or function to provide
business unit-wide solutions. Primary Responsibilities: Researches and recommends new technologies in support of the
strategic direction of the business unit and participates in the
research and recommendation of appropriate models, methods, tools,
and technologies to achieve business-unit-wide solutions. Drives the completion and value generation of large-scale
Artificial Intelligence (AI) projects. Writes production-level code to achieve greater performance. Prototypes and deploys ML solutions, using experimentation
design, generalized linear models, and mixed effect models. Collaborates with senior managers and decision makers to
identify and solve a variety of high-level business problems. Researches, evaluates, and implements appropriate and new
analytical methodologies, approaches, and solutions. Verifies and evaluates effective data/algorithm designs that
fulfill business objects, productivity, and platform
implementation. Applies probability theory and statistical data to identify
significant differences in relationships among sources of
information. Implements models production systems and leverages ML algorithms
to measure business value and customer impact. Formulates and applies mathematical modeling and optimizes
methods to develop and interpret information that assists
management with decision making, policy formulation, and other
managerial functions. Plans and leads organization wide initiatives. Defines measurement frameworks. Partners with industry experts to identify new data science
models used across production systems. Provides leadership, technical supervision, and expertise to
multiple teams in broad technical areas on complex
organization-wide projects. Sets visions, goals, and direction of team/organization. Oversees the technical implementation of cross-divisional or
company architectural components. Education and Experience: Bachelors degree (or foreign education equivalent) in Computer
Science, Engineering, Information Technology, Information Systems,
Mathematics, Business Administration, or a closely related field
and five (5) years of experience in the job offered or five (5)
years of experience prototyping and deploying Machine Learning
solutions into production environments according to Agile
methodologies for institutional clients -- Registered Investment
Advisors (RIAs) and Broker Dealers (BDs). Or, alternatively, Masters degree (or foreign education
equivalent) in Computer Science, Engineering, Information
Technology, Information Systems, Mathematics, Business
Administration, or a closely related field and three (3) years of
experience in the job offered or three (3) years of experience
prototyping and deploying Machine Learning solutions into
production environments according to Agile methodologies for
institutional clients -- Registered Investment Advisors (RIAs) and
Broker Dealers (BDs). Skills and Knowledge: Candidate must also possess: Demonstrated Expertise (DE) analyzing and evaluating Machine or
Deep Learning (ML and DL) models in online advertising (clickstream
data, Adobe, and Google analytics), recommender systems (Bayesian
models, collaborative systems, restrictive boltzman machines, and
reinforcement learning), and user behavior applications (neural
network classifiers and RNNs), using R, Python, or C++; writing
production-level code to achieve greater performance; and
prototyping and deploying ML solutions using experimentation design
-- design of experiments, generalized linear models, and mixed
effect models. DE liaising with business, product, and engineering stakeholder
teams to analyze institutional clients business requirements --
converting requirements to ML/Artificial Intelligence (AI)
solutions and assessing the impact of ML/AI solutions using
experimentation design; and communicating revenue or cost saving
benefits to senior leadership and external clients -- RIAs and
BDs. DE executing data science projects across computing environments
and platforms -- Linux, Windows, Oracle/SQL, Greenplum/Postgres,
and Hadoop/Hive; performing software development -- programming in
Python, using data science libraries (NLTK, SciPy, Scikit-Learn,
NumPy, or Pandas), DL Frameworks (TensorFlow, PyTorch, or Caffe)
and Web frameworks (Django and Flask); building ML models --
supervised, unsupervised, and reinforcement learning in a large
financial services environment; and designing and developing data
pipelines and cleansing data in Amazon Web Services (AWS), Google
Cloud, Azure, and SageMaker, or using On-Premises computing
tools. DE managing end-to-end data science and ML projects, involving
large-scale, multi-dimensional databases, complex business
infrastructure, and cross-functional teams; and developing AI/ML
solutions designed for large institutional clients (RIAs/ BDs). For full job details and to apply, please visit
https://jobs.fidelity.com/ and search for job number 2044481.
Keywords: Fidelity Investments, Providence , Director, Data Science - 2044481, Finance , Boston, MA, Rhode Island