Fidelity - Senior Analyst/Specialist - Advanced Analytics & Data Sciences

Fidelity Overview

Fidelity Investments is one of the world's largest providers of financial services. Founded in 1946, the firm is a leading provider of investment management, retirement planning, portfolio guidance, brokerage, benefits outsourcing and many other financial products and services to more than 20 million individuals and institutions, as well as through 5,000 financial intermediary firms. The firm is the largest mutual fund company in the United States, the No. 1 provider of workplace retirement savings plans, the largest mutual fund supermarket, a leading online brokerage firm and one of the largest providers of custody and clearing services to financial professionals. Business Unit Overview:

Business Analytics & Research (BA&R), a part of FMR India, is a consulting and insights team that enables business leaders at Fidelity Investments to make informed decisions. The team uses a combination of business & investment research, advanced analytics and decision sciences to solve business problems at the operational, tactical and strategic level. The group has a high focus on leveraging big data and technology to facilitate critical decisions, and is in the process of setting-up a first of its kind big data lab in India. The group houses top talent, with over three-fourths of the associates having a post graduate degree or PhD. The group provides a unique exposure to the financial services industry spanning workplace investing, retail investing, institutional investing, asset management and private equity. Role Description

This role involves working with senior stakeholders in understanding and identifying the business requirements and needs in the areas of Big Data Analytics and Artificial Intelligence. Scanning the fast paced external and internal environments in these areas, developing futuristic ideas that would benefit the firm and leading implementation of mathematical/AI models/algorithms/solutions to bring those ideas to life. Specific experience in AI areas like deep learning, genetic algorithms will be an advantage.

Individual in this role is expected to work with multiple stakeholders and teams, have excellent knowledge and experience of recent developments and work in a self-directed manner in ambiguously defined need areas.

Candidate Description

- Candidate should be expert in handling various data types and structures: structured, unstructured, voice, image and video data, static versus streaming data. Extensive prior experience in integrating data, profiling, validating and cleansing data in Big Data platforms is a must

- Should possess extensive knowledge and experience in applying data mining and machine learning, deep learning techniques in a professional context

- Should have extensive experience with relational, NO-SQL and Graph databases

- High level of proficiency in statistical tools and programming environments like SAS, R, Python, Big Data platforms like Hadoop, Spark is a must

- Must possess good programming languages skill in Java/C/C++

- Exposure to Deep Learning applications and tools like Theano, Torch, Caffe, TensorFlow is preferred

- Exposure to Graph Databases like GraphX, Neo4j and semantic web applications will be preferred

- Candidate will be expected to communicate analytical results and developed solutions in a way that is meaningful for business stakeholders and provides actionable insights.

- Have the ability to discover new opportunities where analytical techniques can be leveraged for solving business problems

Behavioral Attributes

- Effective communication and excellent - story-telling from data- abilities.

- Ability to influence stakeholders and provide thought leadership.

- Team management and mentoring skills.

Education and Experience

- 5 - 8 years of relevant experience with organizations known for cutting edge/ best-in-class applications of Advanced Analytics, Predictive Modeling and Artificial Intelligence.

- Master's Degree / PhD in a quantitative field (e.g., Computer Science, Economics, Engineering, Mathematics, Finance, Statistics, Operations Research)