L4 Senior Data Scientist
Role summary
TELUS Advanced Data and Analytics is seeking an experienced Senior Data Scientist with a Master's or Ph.D. in a quantitative field and 3+ years of experience in machine learning. The role involves developing and deploying ML models for customer churn, segmentation, and prospect targeting, analyzing marketing campaigns, and designing A/B tests. Proficiency in Python, ML libraries (TensorFlow, PyTorch, scikit-learn), statistical analysis, NLP, GCP, Oracle, and SQL is required. The candidate will collaborate with stakeholders, translate business needs into data solutions, and present findings. Mentoring junior data scientists is a plus. This role focuses on driving customer retention, segmentation, and sales growth through data-driven insights.
Description
Our team and what we’ll accomplish together:
Our TELUS Advanced Data and Analytics team is seeking an experienced and accomplished Senior Data Scientist to join our team. The ideal candidate has a deep understanding of data analysis, Cloud engineering, machine learning, and statistical modeling, along with a proven track record of delivering impactful insights and solutions.
What you'll do:
- Collaborate with stakeholders to understand the business requirements and translate them into actionable data-driven solutions.
- Manage the comprehensive development and ongoing maintenance of machine learning initiatives aimed at preventing customer churn, segmenting customers, and targeting prospects and new customers
- Analyze the performance of marketing campaigns and identify areas for improvement. By leveraging data insights, optimize campaign targeting, to maximize ROI and achieve marketing objectives.
- Design and analyze A/B tests to evaluate the effectiveness of different marketing strategies, messages, or designs. In order to make data-driven decisions and continuously improve marketing efforts.
- Act as a translator, effectively communicating between the business and data science team to ensure alignment and understanding of business needs, pain points, opportunities of improvements and objectives.
- Design and implement advanced machine learning models and algorithms to analyze large datasets and identify patterns and trends in customer behavior .
- Conduct thorough data analysis and experimentation to validate and optimize the performance of machine learning models.
- Develop and deploy scalable and efficient machine learning pipelines and workflows.
- Collaborate with data engineers and software developers to integrate machine learning models into production systems.
- Present findings and insights to both technical and non-technical stakeholders in a clear and concise manner.
- Mentor and provide guidance to junior data scientists and team members.
Qualifications
What you bring
- Master's or Ph.D. degree in Computer Science, Statistics, Mathematics, or a related field.
- Proven experience 3+ years in developing and implementing machine learning models and algorithms for real-world applications.
- Strong programming skills in Python and experience with popular machine learning libraries such as TensorFlow, PyTorch and scikit-learn.
- Solid understanding of statistical analysis, data mining, predictive modeling and Natural Language Processing techniques.
- Strong experience with data preprocessing, feature engineering, and dimensionality reduction techniques.
- Proficiency in Google cloud platform and distributed computing frameworks, Oracle, SQL and working with relational databases.
- Strong problem-solving skills and the ability to think critically and analytically.
- Excellent communication and presentation skills, with the ability to effectively communicate complex concepts to diverse stakeholders.
- Experience in leading and mentoring a team of data scientists is a plus.
Join our team and contribute to the development of cutting-edge machine learning projects that will drive customer retention, segmentation, and sales increase. Apply now and be part of our data-driven journey towards success!
- Please note that the qualifications and responsibilities mentioned above are just a guideline and can be adjusted based on the specific requirements of your organization.