Data Scientist

Mphasis; Toronto; On-site; CAD 120,000 - 180,000; Full time

Job summary

Mphasis is seeking an experienced Data Scientist in Canada to design, develop and deploy ML models, perform statistical analysis, and build data-driven solutions that impact business outcomes. The role emphasizes collaboration with product, engineering, and business teams to translate requirements into scalable analytics.

The ideal candidate has strong skills in Python, SQL, R, and cloud services, with hands-on experience in ML pipelines, A/B testing, and data visualization to communicate

Qualifications

• Bachelor’s degree in a related field; Master’s preferred.
• 5+ years hands-on experience in data science, ML, or analytics.
• Strong communication skills for presenting insights to senior stakeholders.

Responsibilities

• Design, develop, and deploy ML models to solve business problems.
• Perform data exploration, feature engineering, and statistical analysis.
• Build end-to-end ML pipelines including training, deployment, monitoring.
• Collaborate with product, engineering, marketing, and business stakeholders.
• Conduct A/B testing and experimentation to evaluate model effectiveness.
• Develop dashboards and reports to communicate insights and KPIs.

Skills

Python

SQL

R

Git

communication skills

Education

Bachelor's degree in Computer Engineering / Electrical Engineering / Data Science

Master's degree in Data Science / Analytics

Tools

Databricks

Streamlit

Jira

Excel

Job description

Data Scientist – Job Description (10+ Years Experience)

Job Title: Data Scientist

Experience Level: 10+ years of relevant experience in Data Science, Machine Learning, and Advanced Analytics

Location: Canada

Role Summary

We are seeking a Data Scientist with strong experience in machine learning, statistical modeling, data analysis, and cloud-based data solutions. The ideal candidate will work closely with cross‑functional stakeholders to design, develop, deploy, and optimize data‑driven solutions that drive business impact, improve user experience, and support informed decision‑making.

Key Responsibilities

• Design, develop, and deploy machine learning and predictive models to solve business problems such as personalization, forecasting, anomaly detection, and classification
• Perform data exploration, feature engineering, and statistical analysis on large and complex datasets
• Build and maintain end‑to‑end ML pipelines, including training, deployment, monitoring, and performance optimization
• Collaborate with product, engineering, marketing, and business stakeholders to translate requirements into data solutions
• Conduct A/B testing and experimentation to evaluate model effectiveness and product features
• Develop dashboards and reports to communicate insights, KPIs, and model outcomes to technical and non‑technical audiences
• Optimize data workflows using SQL, ETL processes, and cloud services
• Contribute to data quality, governance, and best practices
• Mentor junior data scientists and contribute to technical knowledge sharing within the team

Required Technical Skills

Programming & Data

• Python (Pandas, NumPy, SciPy, Statsmodels)
• SQL
• R (working knowledge)
• Git / Version Control

Machine Learning & AI

• Supervised and unsupervised learning techniques
• Deep Learning frameworks (PyTorch, TensorFlow, Keras)
• Predictive modeling, classification, regression, time‑series analysis
• Feature engineering and model evaluation
• Computer Vision and NLP exposure (including LLM‑based prototypes)

Data Visualization & BI

• Power BI
• Tableau
• Data visualization libraries (Matplotlib, Seaborn, Plotly)

Cloud & Big Data

• AWS (SageMaker, S3, Lambda, Glue, IAM)
• Spark / Databricks
• MLOps tools (MLflow, CI/CD pipelines for ML)

Tools & Platforms

• Databricks
• Streamlit
• Jira
• Excel / PowerPoint / SharePoint

Required Qualifications

• Bachelor’s degree in Computer Engineering, Electrical Engineering, Data Science, or related field
• Master’s degree in Data Science, Analytics, or a related discipline is preferred
• 5+ years of hands‑on experience in data science, machine learning, or advanced analytics roles
• Strong communication skills with the ability to present insights to senior stakeholders

Nice to Have

• Experience with personalization and recommendation systems
• Experience in revenue, marketing, or user‑behavior analytics
• Exposure to real‑time or streaming data solutions
• Experience mentoring or leading junior team members