Data Analyst/scientist

1 week ago

Remote, Canada SPARKLEX TECHNOLOGIES INC Full time

Programming Skills: Proficiency in programming languages commonly used in data analysis is crucial. These may include Python, R, or SQL. Data Scientists often require more advanced programming skills to develop machine learning models or perform data engineering tasks.

Statistical and Mathematical Skills: A solid foundation in statistics and mathematics is important for data analysis and modeling. Knowledge of concepts such as probability, hypothesis testing, regression analysis, and machine learning algorithms is highly beneficial.

Data Manipulation and Visualization: Experience with data manipulation tools and techniques is necessary. This includes working with data in various formats (CSV, Excel, databases), cleaning and transforming data, and visualizing data using tools like Tableau, Power BI, or matplotlib/seaborn in Python.

Machine Learning: Data Scientists should have a strong understanding of machine learning concepts and algorithms. Experience with building and evaluating models, feature engineering, and model selection and optimization is important.

Database and SQL: Proficiency in working with databases and writing SQL queries is crucial for extracting and manipulating data efficiently. Knowledge of database concepts and familiarity with technologies like MySQL, PostgreSQL, or MongoDB is valuable.

Data Wrangling and ETL: Experience in data wrangling and Extract, Transform, Load (ETL) processes is important for preparing and cleaning data for analysis. Familiarity with tools like Apache Spark or Apache Hadoop is advantageous.

Data Visualization and Reporting: The ability to present data effectively through visualizations and reports is important. Experience with data visualization tools like Tableau, Power BI, or matplotlib/seaborn in Python is beneficial.

Communication and Domain Knowledge: Strong communication skills are essential to effectively communicate findings and insights to non-technical stakeholders. Domain knowledge in the industry or field you are working in is valuable for understanding the context of the data and making informed decisions.

Continuous Learning: The field of data analysis and data science is constantly evolving. Demonstrating a willingness to learn and adapt to new tools, technologies, and methodologies is crucial for success in these roles.

**Job Types**: Full-time, Fixed term contract
Contract length: 12 months

**Salary**: $92,051.00-$98,415.00 per year

**Benefits**:

- Dental care
- Paid time off

Flexible Language Requirement:

- French not required

Work Location: Remote

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