big data analyst.

Randstad Sourceright is a global talent leader, providing solutions and expertise

that help companies position for growth, execute on strategy, and improve

business agility. Randstad Sourceright’s experience encompasses all facets of the talent

acquisition of permanent employees and the contingent and contractor

workforce. Key offerings include Managed Services Provider (MSP) programs,

Recruitment Process Outsourcing (RPO), and Blended Workforce Solutions.

Working for a multi-country organization means working with clients and

colleagues with different backgrounds. This results in a digital way of working

and requires a proactive mindset.

Big Data Analyst

Objective

The Big Data Analyst employs big data technologies and analytics techniques to process and analyze large amounts of data to derive insights and predictions that help improve business decisions.  In order to do this, the Big Data Analyst must be able to organize data, cleanse and normalize raw data, process data for statistical modeling using computers, and identify relationships and trends in data.  The Big Data Analyst must have a strong educational foundation in data analytics, basic machine learning, database technology, and computer programming related to basic data processing/visualization.  The Big Data Analyst must be able to think analytically, and must be detail oriented.  Also, the Big Data Analyst should be able to effectively communicate with supervisors and business leaders who may not have strong data analytics or statistical background.

The Big Data Analyst will usually work independently with guidance provided by the senior team members.

Position Summary

Responsibilities

●      Responsible for data quality and data inspection

●      Create insightful dashboards and data reports

●      Produce query for data preprocessing, feature engineering, and data enrichment

●      Providing recommendation for improvements

●      Using the data to identify problems and propose solutions

●      Defining and evaluating research hypotheses

●      Working with other teams (UX researchers, stakeholders, data scientists) on strategic initiatives

●      Effectively communicating trends, patterns and predictions using relevant data

Technical Requirements:

●      5+ years of experience doing quantitative analysis and visualization reports

●      Ability to work independently but also as a team player

●      Experience with large datasets and the ability to optimize queries

●      Solid understanding of statistics (distributions, probability theory, hypothesis testing)

●      Effective presentation skills and producing clear and extensive documentation (e.g. using Confluence)

●      Proficiency using Excel, SQL, Google BigQuery, PowerBI, and  visualization tools such as Tableau, Domo, Google Data Studio

●      Basic Python, R scripting experience would be an great advantage

Business Requirements

●      Experience – working experience in a corporate environment preferred

●      MI/Business Intelligence/Analytics background is essential

●      Talent Acquisition/MSP/RPO/People Analytics experience is preferred

●      Highly analytical mind and overall curiosity; exploring what's next is a second nature

●      Collaboration: ability to connect to teammates, colleagues and partners from a diverse background and co-create in making a great product

●      Ethics: you are very aware about the ethical aspects concerning data, analytics, ML and AI and approach things from an 'ethics by design' perspective

●      Excellent communication and facilitation skills required for various levels throughout external and internal organizations

●      Ability to prioritize and manage multiple projects, tasks, and meeting deadlines while maintaining quality

●      Ability to synthesize and analyze information and ideas

●      Strong drive and commitment to delivering outstanding results and

●      Ability to navigate ambiguity and work effectively in a fast-paced environment

●      Demonstrated continuous improvement, process documentation, and workflow skills

Education

Bachelors in Math, Physics, Statistics, Economics, Management, Business, Computer or Tech Science, or other quantitative fields

Supervisory Responsibility

Provides guidance, leadership, or training to other employees (no direct supervision)

Organizational Structure:

Job title this position reports: Manager Data Science, Manager ML Engineering