Data Scientist at Spait Infotech

Ontario, Ontario, Canada -

Full Time

Start Date

Immediate

Expiry Date

30 Dec, 26

Salary

50000.0

Posted On

01 Oct, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Yes

Skills

Industry

Consumer Services

Description

Key ResponsibilitiesCollect, clean, transform, and analyze structured and unstructured data.
Identify trends, patterns, and insights from large datasets.
Develop and validate statistical and machine learning models.
Perform exploratory data analysis (EDA) and feature engineering.
Build predictive, classification, clustering, and forecasting models as required.
Evaluate model performance using appropriate statistical and machine learning metrics.
Work with stakeholders to understand business problems and translate them into data science solutions.
Create dashboards, reports, and visualizations to communicate findings effectively.
Collaborate with data engineers, software developers, product managers, and business teams.
Deploy and monitor machine learning models in production where applicable.
Maintain documentation of datasets, models, experiments, and analytical processes.
Continuously research and evaluate new tools, techniques, and machine learning approaches.
Required SkillsStrong programming skills in Python or R.
Good knowledge of statistics and probability.
Strong understanding of machine learning algorithms and concepts.
Experience with libraries such as Pandas, NumPy, Scikit-learn, and visualization tools such as Matplotlib or Seaborn.
Good knowledge of SQL and relational databases.
Experience with data cleaning, preprocessing, feature engineering, and model evaluation.
Strong analytical and problem-solving skills.
Ability to communicate technical findings to both technical and non-technical stakeholders.

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Responsibilities

Key ResponsibilitiesCollect, clean, transform, and analyze structured and unstructured data.
Identify trends, patterns, and insights from large datasets.
Develop and validate statistical and machine learning models.
Perform exploratory data analysis (EDA) and feature engineering.
Build predictive, classification, clustering, and forecasting models as required.
Evaluate model performance using appropriate statistical and machine learning metrics.
Work with stakeholders to understand business problems and translate them into data science solutions.
Create dashboards, reports, and visualizations to communicate findings effectively.
Collaborate with data engineers, software developers, product managers, and business teams.
Deploy and monitor machine learning models in production where applicable.
Maintain documentation of datasets, models, experiments, and analytical processes.
Continuously research and evaluate new tools, techniques, and machine learning approaches.
Required SkillsStrong programming skills in Python or R.
Good knowledge of statistics and probability.
Strong understanding of machine learning algorithms and concepts.
Experience with libraries such as Pandas, NumPy, Scikit-learn, and visualization tools such as Matplotlib or Seaborn.
Good knowledge of SQL and relational databases.
Experience with data cleaning, preprocessing, feature engineering, and model evaluation.
Strong analytical and problem-solving skills.
Ability to communicate technical findings to both technical and non-technical stakeholders.