Client Relationships

2 days ago


Malaysia Exness jobs for internal candidates Full time 120,000 - 250,000 per year

Why this role matters

Collect, process, and analyze data to generate actionable insights supporting data-driven decision-making across the Client Relationships & Service Division organization. The role involves identifying trends, uncovering patterns, causal Inference, and creating visualizations or reports to communicate findings effectively to stakeholders, driving improvements in operations, strategy, and performance.

The role is based in our office in Kuala Lumpur, Malaysia. In case of relocation, we offer full relocation support for you and your family to make your move smooth and worry-free.

What you'll actually do
  • Define and enhance metrics that represent product performance and operational efficiency.
  • Collect data from multiple sources, ensuring accuracy, completeness, and usability.
  • Clean, organize, and transform raw data into structured formats suitable for analysis.
  • Identify inefficiencies in processes and propose effective, data-driven solutions.
  • Assess proposed solutions using backtesting, A/B testing, and modeling techniques.
  • Conduct exploratory data analysis (EDA) and hypothesis testing to validate insights.
  • Collaborate with Data Engineers to improve the data ecosystem and maintain comprehensive knowledge of available datasets.
  • Create effective visualizations and reports (e.g., dashboards) to communicate findings to stakeholders.
Who we're looking for
  • Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
  • Minimum of 4 years of hands-on experience in data science.
  • Proven track record in causal inference methods, A/B test design, and interpretation of results.
  • Comprehensive understanding of mathematical statistics and probability theory, including correlations, effects, and anomaly detection.
  • Proficiency in SQL and Python (pandas, visualization, and ML packages).
  • Understanding of statistical methods, predictive modeling, and machine learning techniques.
  • Expertise in machine learning and mathematical modeling for data analysis and decision-making.
  • Ability to perform exploratory data analysis (EDA) and hypothesis testing.
  • Experience with Spark (plus).
  • Experience with Metabase and Grafana (plus).
  • Experience in Agile environments or collaborating with development teams (plus).
  • Strong team player.
  • Highly organized and rigorous thinker, able to solve problems diligently and creatively.
  • Detail-oriented and results-oriented.
  • Fast learner with ability to work independently.
  • Adaptable to changing requirements and able to produce quick, effective solutions.
What we offer along the way
  • Competitive salary and annual performance bonus
  • Full relocation support for you and your family — flights, housing, visas, and legal assistance included
  • Top-tier health insurance with full family coverage — medical, dental, vision, mental health — plus life insurance for peace of mind
  • Unlimited learning opportunities: external courses, English lessons, career and leadership development
  • Education allowance covering school and kindergarten fees
  • 21 working days of annual leave, plus public holidays and fully paid sick, maternity, and paternity leave
  • Employee appreciation program: branded gifts, birthday day-offs, celebration budgets for weddings, newborns, and milestones
  • "Get to know Team" trips — meet colleagues across our global hubs, along with company-wide offsites that raise the bar
  • Employee share scheme — grow with us
  • Meal and transport allowance
  • Monthly wellness allowance for your sport or fitness of choice
  • Holiday flight and accommodation coverage after 1 year of service
What your journey looks like
  1. Intro call with Recruiter (30 minutes)
  2. Tech interview (90 minutes)
  3. Behavioural interview (60 minutes)

Please use your exness work email for internal applications and ensure to disclose any existing Conflict of Interest you may have.



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