Data Scientist

Princeton, NJ, USA | Mercer

  • Industry:
    Management Consulting
  • Position Type:
    Full-Time
  • Functions:
    IT / Information Technology
  • Experience:
    3-5 years
Job Description:
127 people have viewed this job

Mercer is seeking an exceptional Data Science professional to leverage the vast amounts of data assets about our customers to develop powerful insights that drive the firm’s go-to-market effectiveness while delivering better value for our customers through insight-driven products, services and solutions that help them address current and anticipate future needs.


This is a unique opportunity to join a new, multidisciplinary team of creative and passionate individuals tasked with developing a suite of next-gen insight-driven solutions utilizing the latest Big Data technology and innovative data science approaches including machine learning techniques.


We’re a lean, flat and agile Big Data Analytics team combining data science and engineering to identify high-value with the greatest commercial impact. The team works in quick iterations, using the techniques and algorithms best suited for solving the challenging problems of clients.


In this global role, your primary focus will be in applying data mining techniques, doing statistical analysis, automating scoring using machine learning techniques and building recommendation engines integrated with our products or internal business processes.


The ideal candidate is passionate about asking and answering questions in large datasets, able to communicate that passion to product managers and engineers, and has a keen desire to solve business problems.


Responsibilities


Develop advanced analytics, predictive models and machine learning algorithms. Work with internal and external business stakeholders to uncover actionable insights from Mercer client and prospect data

Design and build machine learning and algorithms; conduct analyses at the appropriate level of complexity to produce relevant results for the business. Build and maintain analytics data pipelines

Partner with Digital Platform team to evolve a Mercer Hadoop Data Lake environment (branded as Knowledge Fabric) which encompasses all Mercer major data sources to be leveraged for commercialization and provides a computing environment on the top. Advise on data science use cases for Knowledge Fabric evolution.Advise on selection of technology suitable for Mercer business applications

Provide analytical and data support to engineering teams for setting up data repository and transforming unstructured data

Build business intelligence and visualization.Develop key business metrics and dashboards to support optimization of Mercer internal processes, as well as ROIs.Create visualization to present analysis findings to business stakeholders.Contribute to product development with graphic representation and insight interpretation tools

Qualifications


MS, or PhD (preferred) in Data Science, Computer Science, Mathematics, Statistics, Operations Research or other quantitative fields

4+ years of experience building predictive and descriptive model2+ years of experience with Apache Hadoop and Spark ecosystems of open-source tools. Our data processing and modeling pipelines are built using Horton works platform

2+ years of hands-on BI development experience with major commercial BI tool

Experience with NoSQL databases, such as HBase, Cassandra, MongoDB is a plus

Experience working with Amazon Web Services is a big plus

Hands-on experience with Python, R, Matlab, Scala, SAS, or other related analytical/programming tools or software

Proficient in machine learning techniques (such as k-NN, Naive Bayes, SVM, Decision Forests, etc.) and their application in business areas

Understanding of RDBMs and SQL programming skills, such as PostgreSQL, MySQL, MSSQL, Oracle SQL/PLSQL

Experience with web services such as AWS S3, DigitalOcean, Redshift and Spark; ability to connect data using SOAP API, REST API, and web crawling techniques

Firm grasp of Big-Data Platforms and modeling frameworks, especially Spark and Hadoop; comfortable dealing with large data sets within a distributed computing environment (Hadoop, Hive/PIG, HBase, etc.

Knowledge of any data visualization and reporting tools, such as D3, Qlik (View or Sense), Tableau, MS PowerBI, SAP Business Objects, or MicroStrategy

Ability to communicate complex analytical insights in a simple, concise manner and to build strong relationships with marketing and product teams to effectively convert insights into action

Strong communication skills

Excellent organization and prioritization skills

Working knowledge of Apache NiFi for data ingestion is a plus

Passionate about asking and answering questions in large datasets, and capable of communicating that passion to product managers and engineers

Thrive in a fast paced, test-driven, collaborative and iterative engineering environment

AWS Cloud Solution Architect certificate is a plus