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21F The Globe Tower
Live, first seen by us 85 days agoEmployment type in the employer’s posting: Full timeFrom the employer’s posting
Build, test and deploy machine learning and statistical models
Track accuracy, drift and business value of deployed models
Build data pipelines combining telco, digital, social and external data
Turn model outputs into insights and campaign or operational strategies
Lead data extraction, cleansing and feature engineering on large datasets
Build, test, and deploy machine learning and statistical models that address business needs
Track performance, accuracy, drift, and business value of deployed models
Build frameworks and data pipelines that combine telco datasets with digital, social, and external data sources to create a holistic customer view.
Translate model outputs into clear insights, actionable recommendations, and campaign or operational strategies
Lead data extraction, exploration, cleansing, and transformation of large and complex datasets
Scripting or programming experience: familiarity in programming languages with relational databases (e.g. Python, Java, Ruby, Clojure, Matlab, Pig, SQL);
Degree in quantitative discipline such as Statistics, mathematics, Operations Research, Engineering, Computer Science, Econometrics or Information Science such as Business Analytics or Informatics
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Day 85
Up longer than most. Similar jobs usually come down between day 7 and day 53.
From 7,797 similar postings that came down. Coming down is not always a hire.
17 open jobs
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- Must possess core competencies, deep understanding and relevant experience in - Scripting or programming experience: familiarity in programming languages with relational databases (e.g. Python, Java, Ruby, Clojure, Matlab, Pig, SQL); - Statistical Analysis: advanced usage of off-the-shelf tools such as R, SAS, SPSS, Weka and other analytical tools or software
- Scripting or programming experience: familiarity in programming languages with relational databases (e.g. Python, Java, Ruby, Clojure, Matlab, Pig, SQL); - Statistical Analysis: advanced usage of off-the-shelf tools such as R, SAS, SPSS, Weka and other analytical tools or software - Big Data: Experience with Big data tools such as HDFS, Cassandra, Storm
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We file this job under Data Leadership, by the work the posting describes.
Data leaders run data teams or design how a company's data fits together. Managers hire, set priorities and answer for whether the data work pays off; architects choose the systems and the shape of the data.
Expect years of hands-on data work, experience leading people or projects, and the ability to explain tradeoffs to executives.
Unlike a senior engineer or analyst, most of a data leader's week goes to people, planning and decisions rather than building.
The government has no code for data leaders, so these figures are for the closest group, computer and information systems managers, which includes data processing and data operations managers.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 11-3021.
At Globe, our goal is to create a wonderful world for our people, business, and nation. By uniting people of passion who believe they can make a difference, we are confident that we can achieve this goal.
DUTIES AND RESPONSIBILITIES:
Data Exploration & Feature Engineering
Lead data extraction, exploration, cleansing, and transformation of large and complex datasets
Design, engineer, and validate features needed for predictive models and advanced analytics
Build frameworks and data pipelines that combine telco datasets with digital, social, and external data sources to create a holistic customer view.
Model Development & Performance Management
Translate business problems into clear data science approaches and model requirements
Build, test, and deploy machine learning and statistical models that address business needs
Track performance, accuracy, drift, and business value of deployed models
Conduct periodic model tuning and ensure continuous improvement aligned with ROI goals.
Insights, Applications & Business Enablement
Translate model outputs into clear insights, actionable recommendations, and campaign or operational strategies
Identify new opportunities to apply data science, especially in customer behavior prediction, segmentation, and credit risk scoring.
Partner with business teams to embed analytics solutions into decision-making and customer lifecycle programs.
REQUIREMENTS:
Work Experience
Minimum of three (3) years’ experience in customer analytics domain and/or credit risk assessment and financial services, covering most of the following: data mining, predictive modeling, machine learning, statistical modeling and analysis, large scale data acquisition, transformation, and cleaning, both structured and unstructured data
Proven track record of leading and collaborating on advanced analytics strategic initiatives; Proven track record of operationalization of analytic models in collaboration with marketing/risk and IT teams
Worked with large, unfiltered data sets or data science research
Level of Knowledge
Has Knowledge of both structured and unstructured data
Must possess core competencies, deep understanding and relevant experience in
Scripting or programming experience: familiarity in programming languages with relational databases (e.g. Python, Java, Ruby, Clojure, Matlab, Pig, SQL);
Statistical Analysis: advanced usage of off-the-shelf tools such as R, SAS, SPSS, Weka and other analytical tools or software
Big Data: Experience with Big data tools such as HDFS, Cassandra, Storm
Database knowledge: skilled in structured database
Familiar with most of the following disciplines:
Conceptual modeling: to be able to share and articulate modeling;
Predictive modeling: most of the big data problems are towards being able to predict future outcomes;
Hypothesis testing: being able to develop hypothesis and test them with careful experiments;
Natural Language Processing: the interactions between computer and humans;
Machine learning: using computers to improve as well as develop algorithms;
Statistical analysis: to understand and work around possible limitations in models.
Education
Degree in quantitative discipline such as Statistics, mathematics, Operations Research, Engineering, Computer Science, Econometrics or Information Science such as Business Analytics or Informatics
Equal Opportunity Employer
Globe’s hiring process promotes equal opportunity to applicants, Any form of discrimination is not tolerated throughout the entire employee lifecycle, including the hiring process such as in posting vacancies, selecting, and interviewing applicants.
Globe’s Diversity, Equity and Inclusion Policy Commitment can be accessed here
Make Your Passion Part of Your Profession. Attracting the best and brightest Talents is pivotal to our success. If you are ready to share our purpose of Creating a Globe of Good, explore opportunities with us.
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21F The Globe Tower
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