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Total Rewards Analyst, Kraków

Reporting to our Global Compensation/Total Rewards Partner, you will help design and deliver our compensation/total rewards offerings to the company. You will work with our multiple teams to design and implement Reward programs in line with overall OANDA’s business strategy and philosophy.

Specific Duties:

The key responsibilities include:

  • Maintaining and administering key compensation databases and tools
  • Participating in compensation/total rewards/wellbeing surveys to analyze competitive salary information and improve our compensation/total rewards/wellbeing programs.
  • Applying analytic outcomes to transform raw people/compensation/total rewards data into meaningful and actionable compensation/total rewards insights.
  • Contributing to the development of base salary, bonus programs
  • Contributing to the development of compensation/total rewards/wellbeing policies and practices
  • Performing support activities to administer job architecture.
  • Designing and executing data models using statistical principles (e.g., regression, correlation, etc.)
  • Supporting business needs through analysis during the annual and mid-year review cycle.
  • Producing concise, story-centered presentations to communicate analytic insights.
  • Creating, maintaining, and updating interactive data dashboards and visualizations.
  • Conducting in-depth competitive analyses and modeling for total rewards programs, including salary increases, internal pay equity analysis, competitive assessments of market pay trends and budget impact.
  • Running monthly/quarterly/annual total rewards reports/metrics for management reporting purposes as needed.
  • Contributing to the streamlining of our people data infrastructure and processes to ensure consistently high-quality data.
  • Ensuring accuracy and quality of information/analytics produced.
  • Assist Global Total Rewards Partner in any other project/activity when requested.

Qualifications & Requirements:

  • Academic background with a focus on quantitative methods/statistics, business informatics, mathematics
  • Profound knowledge in statistics
  • 3-4+ years of relevant work experience in a role requiring application of analytics skills in a business analyst, data analyst, or statistical analyst role.
  • Having advanced technical acumen in research, statistics, and data analytics methodologies is required.
  • Proficiency in using software such as Tableau, QuickSight, Excel-Power Query, Power Pivot, and Power BI, VBA is required.
  • Knowledge of programming languages such as SQL, Python or R is desirable.
  • Solid applied statistical and analytical skills to design and execute predictive, descriptive, and inferential statistics.
  • Proven ability to adapt and work effectively in a matrix organization with competing deadlines.
  • Proficiency in acquiring, organizing, cleansing, and manipulating large amounts of data.
  • Positive attitude, enthusiastic and self-motivated.
  • Good organizational and time management skills.
  • Commitment to constant improvement of processes.
  • Ability to work closely with other teams and drive strategic aims.
  • Strong work ethic with a “can do” attitude and a customer-focused mindset.
  • Ability to manage competing priorities in a fast-paced environment and deliver desired results.
  • Ability to work independently, initiate and identify solutions.

Why you’ll love working with us:

  • Opportunity to grow within a well-established organization at its newest location.
  • Attractive benefit package
  • We are a learning organization and provide Learning & Development allowance
  • Work with dynamic, passionate and creative teams
  • Flexible working time

Covid support section

  • We are in the new office space which was designed and rebuilt to offer you a secure environment in pandemic time
  • Hybrid way of working (remote work + open office)

What is our application process? Design to current mobile first environment- video calls and possibility of using LinkedIn profile instead of resume. Let us know you!