Data Scientist at Apptoza Inc

Ontario, Ontario, Canada -

Full Time

Start Date

Immediate

Expiry Date

29 Dec, 26

Salary

45000.0

Posted On

30 Sep, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Yes

Skills

Industry

Consumer Services

Description

Key ResponsibilitiesAnalyze large and complex datasets to identify trends, patterns, and business insights.
Develop data science solutions using Python and relevant data science libraries.
Perform data cleaning, preprocessing, feature engineering, and exploratory data analysis.
Develop and optimize data processing pipelines using PySpark.
Build, test, and validate statistical and machine learning models.
Work with structured and unstructured data from multiple sources.
Perform model evaluation, tuning, and performance optimization.
Collaborate with data engineers, business analysts, and application teams.
Present analytical findings and model results to technical and business stakeholders.
Maintain documentation for data models, analysis, methodologies, and processes.
Monitor model performance and identify opportunities for improvement.
Required SkillsStrong hands-on experience with Python for Data Science.
Strong experience with PySpark and distributed data processing.
Good knowledge of Pandas, NumPy, and Scikit-learn.
Strong understanding of statistics, data analysis, and machine learning concepts.
Experience with data preprocessing, feature engineering, and model development.
Good knowledge of SQL and relational databases.
Experience working with large datasets and big-data environments.
Strong problem-solving and analytical skills.
Good communication and stakeholder management skills.

Responsibilities

Key ResponsibilitiesAnalyze large and complex datasets to identify trends, patterns, and business insights.
Develop data science solutions using Python and relevant data science libraries.
Perform data cleaning, preprocessing, feature engineering, and exploratory data analysis.
Develop and optimize data processing pipelines using PySpark.
Build, test, and validate statistical and machine learning models.
Work with structured and unstructured data from multiple sources.
Perform model evaluation, tuning, and performance optimization.
Collaborate with data engineers, business analysts, and application teams.
Present analytical findings and model results to technical and business stakeholders.
Maintain documentation for data models, analysis, methodologies, and processes.
Monitor model performance and identify opportunities for improvement.
Required SkillsStrong hands-on experience with Python for Data Science.
Strong experience with PySpark and distributed data processing.
Good knowledge of Pandas, NumPy, and Scikit-learn.
Strong understanding of statistics, data analysis, and machine learning concepts.
Experience with data preprocessing, feature engineering, and model development.
Good knowledge of SQL and relational databases.
Experience working with large datasets and big-data environments.
Strong problem-solving and analytical skills.
Good communication and stakeholder management skills.