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Data Analyst

Company
Vlink Inc
Nominal Salary
To be agreed
C

Perform data science project development processes, including Exploratory Data Analysis, data cleansing, model development, and deployment using a combination of SQL and R/Python.
Conduct exploratory research/analysis to determine the best fit model to solve a particular business problem.
Monitor the performance of the model in the production environment

Continuously improve the process for model development, validation, and analysis

Present findings to the team and business unit through visual data story-telling

Collaborating actively across functional partners and senior management to accomplish various project objectives

Develop descriptive analytics visualization to support self-service BI platform development

Develop Data Mart tables to support self-service BI platform development
At least 3 years of experience working in analytics role such as Data Analyst or Data Scientist

Bachelor/Masters level in the field of computer science / machine learning / applied statistics / mathematics

Experienced in using multiple data science methodologies to solve complex business problems

Experienced in doing statistical analysis, developing machine learning models into production

Experienced in programming skills in Python/R, data manipulation (SQL, Spark, Pandas) and machine learning (scikit-learn, XGBoost, Keras/Tensorflow) tools

Understanding of relevant statistical measures such as confidence intervals, the significance of error measurements, development and evaluation data sets, etc.
Possess great design and problem-solving skills, have a passion for quality and engineering excellence at scale

Ability to work independently in a fast-paced, iterative development environment

Familiar or experienced in working with ETL/ELT tools such as Pentaho, Airflow, DBT, Dagster

Familiar or experienced in working with BI visualization tools such as Tableau, Power BI, Looker, Google Data Studio, Metabase, Apache Superset
- Exemplary communication skills, ability to work with large cross-functional teams of technical and non-technical members

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