Associate Data Analytics
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Associate Data Analytics
Location
Huamak
Experience
Entry
Posted
Jul 10, 2026
Apply by
August 1, 2026
Applicants
0
Early applicantEasy applyFull-timeWork from Office
Job Description
It's fun to work in a company where people truly BELIEVE in what they are doing!
We're committed to bringing passion and customer focus to the business.
**Job Summary**
Data Scientist is responsible for modeling complex business problems and discovering insights using quantitative techniques (statistical learning, data mining, optimization etc.) Data Scientist often predict or classify situation and develop next best action models. DS scope of work often cover predictive and prescriptive analytic.
**Job Description:**
1. Collaborate across the business to understand IT and business constraints Work with product team and data engineer to plan and design data collection strategies, procedures and policies.
2. Understand new data sources and process pipelines, and catalog/document them.
3. Help to create data pipelines for more efficient and repeatable data science projects.
4. Apply statistical analysis and visualization techniques to various data, such as hierarchical clustering, T-distributed Stochastic Neighbor Embedding (t-SNE), principal components analysis (PCA).
5. Construct and test hypothesis regarding an underlying mechanic of business process.
6. Apply various ML and advanced analytics techniques to perform classification or prediction tasks
7. Testing of ML models, such as cross-validation, A/B testing, bias and fairness.
8. Collaborate with ML operations (MLOps), data engineers, and IT to evaluate and implement ML deployment options.
**Qualification:**
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
Key Responsibilities
- Collaborate with product teams and data engineers to plan and design data collection strategies and policies.
- Understand new data sources and process pipelines, and catalog or document them.
- Create data pipelines for efficient and repeatable data science projects.
- Apply statistical analysis and visualization techniques such as hierarchical clustering, t-SNE, and PCA.
- Construct and test hypotheses regarding underlying business process mechanics.
- Apply machine learning and advanced analytics techniques for classification or prediction tasks.
- Test ML models using cross-validation, A/B testing, and bias/fairness evaluation.
- Collaborate with MLOps, data engineers, and IT to evaluate and implement ML deployment options.
Skills Required
Statistical AnalysisData MiningOptimizationPredictive AnalyticsPrescriptive AnalyticsMachine LearningAdvanced AnalyticsHierarchical Clusteringt-SNEPrincipal Components AnalysisCross-validationA/B TestingBias and Fairness EvaluationData Pipeline DevelopmentCollaborationCommunication
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