Project Management – Analytics

We are hiring Systems Implementation Project Managers with Analytics. Please see the following details as well as the link at the bottom of this page for more information.


Sharing two profiles – the first is more adept in the data management (technical) side while the other is more focused on predictive analytics and modelling.

SI – Analytics (Predictive Analytics and Modeling)


Key Responsibility:

  • Responsible for manipulating and parsing raw, complex data streams to prepare for loading into an analytical tool.
  • Responsible for delving into data from systems in complex formats to discover hidden relationships and useful information at different timescales.
  • Works with key stakeholders to implement machine learning strategies and data mining to develop models of suspicious or anomalous behaviour and identify key parameters.
  • Responsible for identifying areas worth further data driven fraud analysis and provide assessments for key customers.
  • Works with solution development team to define and implement analytics, user interface anddata management.
  • Responsible for designing systems that perform and scale well in large-scale, data-heavy applications.
  • Monitors model performance and makes recommendations for adjustments to increase accuracy.
  • Responsible for documenting implementation details including model choices, rationale, and reasoning.
  • Demonstrates and delivers rapid prototypes as well as fully-tested mature products.



  1. Minimum of six (6) 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
  2. Proven track record of leading and collaborating on advanced analytics strategic initiatives
  3. Proven track record of operationalization of analytic models in collaboration with marketing/risk and IT teams
  4. Worked with large, unfiltered data sets or data science research
  5. Degree in quantitative discipline such as Statistics, mathematics, Operations Research, Engineering, Computer Science, Econometrics or Information Science such as Business Analytics or Informatics
  6. Has Knowledge of both structured and unstructured data
  7. Must possess core competencies, deep understanding and relevant experience in:
    1. Scripting or programming experience: familiarity in programming languages with relational databases (e.g. Python, Java, Ruby, Clojure, Matlab, Pig, SQL)
    2. Statistical Analysis: advanced usage of off-the-shelf tools such as R, SAS, SPSS, Weka and other analytical tools or software
    3. Big Data: Experience with Big data tools such as HDFS, Cassandra, Storm
    4. Database knowledge: skilled in structured database
  8. Familiar with most of the following disciplines:
    1. Conceptual modeling: to be able to share and articulate modeling;
    2. Predictive modeling: most of the big data problems are towards being able to predict future outcomes;
    3. Hypothesis testing: being able to develop hypothesis and test them with careful experiments;
    4. Natural Language Processing: the interactions between computer and humans;
    5. Machine learning: using computers to improve as well as develop algorithms;
    6. Statistical analysis: to understand and work around possible limitations in models.


SI – Analytics (Data Management)

  • Understands and analyzes the data needs of different business units and provides point of view and suggestions as a subject matter expert
  • Design, develop, communicate and implement a data management strategy and framework that meets objectives for the client organization
  • Ensures that a robust process and technology is designed and in place to support strategy and business needs
  • Champions the importance of data processes, data integrity, security, cleanliness, and the strategic use of data within the enterprise
  • Build relationships with key senior stakeholders and as appropriate, exhibit influence and drive change across the company as it relates to managing and leveraging data
  • Provide senior level technical consulting to application development teams during application design and development for highly complex and critical data projects



  • Minimum 10 years’ experience as Database Manager
  • Experience building, motivating and leading teams to solve problems and deliver high quality results in a fast-paced, unstructured environment
  • Experience developing software solutions to build out capabilities on a Big Data and other Enterprise Data Platforms
  • Experience with the various tools & frameworks that enable capabilities within the Hadoop ecosystem (MapReduce, YARN, Pig, Hive, Hbase) and NoSQL
  • Experience designing, developing, and implementing ETL and relational database systems
  • Experience working with automated build and continuous integration systems (Maven, Jenkins) and test-driven development and unit testing frameworks (jUnit, xUnit, Nose)
  • Experience with UNIX/Linux including basic commands, shell scripting and system administration/configuration
  • Experience with data mining, machine learning, statistical modeling tools or underlying algorithms
  • Superior communication, presentation and interpersonal skills
  • Should have led at least 6-8 end to end data management initiatives
  • At least 10 years of experience in Data Management Practices
  • At least 10 years of experience in leading customer engagement and people management
  • 1 year Experience with new data technologies such as Hadoop, Python, Hive, Tableau, etc


Level of Knowledge

  • Bachelors or Masters Degree in Information Technology, computer Science or equivalent /related degree
  • Have Project Management certification (PMP) or other relevant Professional IT courses /certification
  • Understanding of OSS, BSS, eTOM & DWH framework
  • Knowledge of various internal and external data & reporting platforms for telcos
  • Strong understanding of Datawarehouse functionality and tools.