The successful candidate is an experienced generalist data scientist with at least a masters degree in a numerate field and commensurate professional experience. He/she is comfortable in handling end-to-end delivery of various advanced analytics solutions using best-of-breed open source and proprietary technology stack, models and methodologies; juggling competing priorities; preparing and presenting research findings; helping with pre-sales activities; and building complex visualization dashboards and presentations. Beyond technical responsibilities, we are looking for someone who is client-facing, goal-oriented, creative, curious, intellectually-driven, practical, purposeful, an eager and independent learner, and willing to take on new challenges and grow both technically and personally.
- Advanced degree in behavioral science, statistics, physics, math, or another quantitative field
- Strong grasp of probability, statistical inference, optimization algorithms, linear algebra, and calculus
- Understanding of how and when to apply different Machine Learning algorithms
- Ability to write production-level code in Python or R, as well as proficiency with SQL and other high-level programming languages
- Strong grasp of R and/or Python ecosystems (Pandas, NumPy, SciPy and Scikit-Learn Python packages), as well as other analytics packages in Python, R or Spark
- Demonstrable analytical and problem-solving abilities, coupled with an inquiring mind and the ability to learn quickly
- Experience or familiarity designing and running both simulated and live experiments to drive KPI improvement
- Experience or familiarity building supervised and unsupervised models using statistical or machine learning approaches
- Familiar with developing complex UI/UX and highly-interactive data visualization dashboards (e.g. plotly, Bokeh, shiny)
- Hands-on experience in developing and consuming high volume data pipes and high-performance APIs
- Ability to creatively problem-solve, and to thrive in a highly collaborative, multidisciplinary environment
- Partner with clients and other internal stakeholders to frame data and advanced analytics problems both mathematically and within the business context
- Partner with Engineering and DevOps teams to bring models to production
- Debug, maintain, tune, and improve model behavior and performance with live data
- Develop data and solution architectures as well as the solution stack and IT infrastructure that will meet clients’ current and future workloads
- Oversee and facilitate the training of a range of ML models as well as evaluate the quality of the trained models, using existing and new measures
- Report on the current and historical states of client models
- Develop complex, efficient and highly-interactive data visualizations and presentations
- Quickly conduct needs and gap analysis, prototype branded solutions and actively contribute in the pre-sales process
Everuz is a Toronto-based technology services company that makes technology more accessible and powerful for enterprises of all sizes and industries through finely-tuned services and transformational digital solutions. We help companies conceive, design, implement and run their practical digital transformation strategies cost-effectively. Our expertise includes cloud computing, SAP services, big data solutions and custom software development services. We enable our customers to operate profitably, adapt continuously, and grow sustainably.
If you have the required experience, skills and the drive to succeed, please apply now.
|Job Category||Data Science|