BI Data Scientist

Hybrid(1 day on-site, 4 days WFH)

Location: Taytay and San Mateo

Salary: 72,000 - 90,000

BI Data Scientist Bell’s forward-thinking Customer Operations team is creating the ultimate service experience for our residential, wireless and small business consumers. We lead strategic development and execution of day-to-day operations, develop tools and processes to drive service enhancements, manage customer loyalty and retention, and leverage big data and artificial intelligence to create intellectual property. 

As a Data Scientist on this team, you will support the development of statistical and machine learning models, working closely with machine learning engineers to launch these models at scale. You will work with exabytes of rich datasets to develop decision making models that provide recommendations for our customers. 

Job Duties/Accountabilities:

• Degree in a discipline such as: Data Science, applied math, applied science / engineering, economics/econometrics, management science / operations research, or related area 

• You have development experience with at least one general programming language (e.g. Python, C/C++, Java) 

• You have previous experience with ML frameworks (e.g. Scikit-learn, Keras, Tensorflow)

• Drive the creation of machine learning algorithms in the areas of: • Customer Behaviour 

• Customer Segmentation and clustering 

• Mining and analyzing data from company databases to improve marketing, product development, or overall business strategies 

• Using predictive modeling to optimize revenue growth, marketing campaigns, and customer experiences 

• Developing A/B testing campaign frameworks and testing model quality 

• Communicating and coordinating with teams to implement data-driven strategies while measuring progress

Critical Qualifications/Competencies: 

• ML technical expertise (frameworks and libraries): 

• GCP Vertex AI Platform 

• Python development skills 

• Experience with general ML/Data Science tools in Python: numpy, pandas, sklearn, jupyter etc

For Internal Use

• Hands-on experience and expertise with different AI/ML frameworks such as Keras, Pytorch, TensorFlow, SparkML, Scikit-Learn

• Computer science fundamentals 

• Database: SQL, Hadoop Theoretical Knowledge: 

• Advanced knowledge of ML models: deep learning, reinforcement learning, and others 

• Theoretical understanding of neural networks, backpropagation, and optimization algorithms with emphasis on mathematical understanding. 

• Mathematical understanding of some ML algorithms: regression, SVM, decision trees, etc…

Hiring Process:

Initial Interview, 

HM CV review

Cultural interview 30 mins, live code test 30 mins= (1hr)

Take home mobile exam for 3 days

Final Interview -technical related to exams

JO

We offer great benefits

HMO +2 free dependents upon hire

Performance incentives (March &Sept)

VL 15, 15 SL both convertible cash

Optical reimbursement

Education Assistance - reimbursable

Life Insurance upon hiring

6 mos paid leave maternity and paternity