Data Scientist

Job description

Incentivio is unique in the restaurant tech space. Growing 250%+ YoY, Incentivio is set to break the norms of how restaurants drive guests to their business! As restaurants continue to struggle with labor shortages, 3rd party delivery economics and juggling a complex tech stack, Incentivio’s market leading data-driven engagement and analytics platform is designed to help restaurant’s reclaim their guests, data, and brand awareness while continuing to grow and thrive!

Incentivio is a fast-growing startup that helps restaurants increase revenue and margins by owning the digital guest experience - from branded mobile apps to online ordering, loyalty, delivery, analytics, and much more. Our cloud-based platform allows restaurants to launch branded digital guest experiences in weeks, and our restaurant clients hail from all over North America - from Florida to Montreal and British Columbia to San Diego. We're looking for hard-working, self-motivated individuals to join our growing team (70+ team members) and help us make a difference in the restaurant industry!

As the first full time member of Incentivio’s data science team, you will be responsible for the design, development and delivery of analytic solutions. In this newly created role you will serve as a liaison between business and technical teams to drive results and enhance value through improved delivery of impactful analytic insights, improved data visualization and statistical analysis. The candidate will use new technologies to develop and deliver solution-oriented products that drive innovation in our business and provide a state of the art experience for both restaurant operators and customers.

Essential Job Functions

  • Collaborate with key internal and external stakeholders to gather and analyze needs and requirements;

  • Conduct analyses of the data, ranging from descriptive ad-hoc analyses to in-depth investigations and outcomes with a variety of statistical modeling approaches;

  • Construct and deliver written reports of the analytic findings in a variety of formats (reports, PPT, including visualization of data and findings, formulate recommendations), and effectively present the results to with non-analytic audiences;

  • Efficiently implement the models in a variety of modeling tools, striving for highly accurate models.

  • Understand the underlying statistical concepts and computational approaches that enable efficient execution of models and may be able to design and implement modifications and enhancements to the computations.

  • Tailor the analytic solution to the specific need and constraints of delivery timelines;

  • Apply creativity in developing analytic solutions based on available data sources, and in representing analytic findings in reports, tools, and other media to support most effective translation and application of internal and external customers.

  • Your experience will also consist of developing innovative analytic approaches leveraging all available internal and external data sources

Job requirements

To be considered for this challenging analytic opportunity, your experience will consist of a minimum of 5 years of analytics experience. Your experience will also consist of the following:

  • 3+ years of experience as a Data Scientist in the E-Commerce industry (Required) 
  • Deep knowledge of coding in statistical packages (like Python, R and SAS) with strong quantitative skills, including relevant experience in classification, regression, cluster analysis, time series analysis, probability & statistics, and experimental design

  • Proficiency in processing large datasets (measured in hundreds of millions or billions of records) using languages like SQL & MongoDb.

  • Experience working with a product management team to identify desired outcomes, approach, and implementation

  • Advanced skills and training in machine learning concepts and other quantitative research analytics such as: Ensemble Models, Neural Networks, Feature Engineering, Non-Linear Regression Analysis, Multivariate Analysis, Bayesian Methods etc.

  • Experience working with data visualization platforms (e.g., Tableau, PowerBI and Microstrategy)

  • Experience with cloud-based services (preferably AWS).

  • Experience with Microsoft Office or Google Business Suite products

  • Demonstrated experience in working with business partners and/or clients to identify the business problem, identifying proper data, constructing analytic solutions to the business problem and then presenting the data insights along with creative recommendations;

  • Experience in developing analytical tools, templates, and financial/statistical models

  • Ability to quickly develop knowledge and understanding of new domains and underlying data sources;

  • Experience in translating business problems across disciplines into advanced analytic projects with measurable business value.

  • Experience with theoretical modeling approaches and matching analytic modeling approaches to a wide range of business applications.

  • Familiarity with deep learning techniques (ANN, CNN, LSTM etc.).

  • Good Understanding of state-of-the-art NLP techniques (language models, NER, information extraction, word embeddings etc.)

  • Familiarity with Recommender Systems.

  • Competent in using machine learning libraries/frameworks like scikit-learn, TensorFlow, PyTorch, HuggingFace.

  • Experience with model evaluation, validation, and deployment techniques to ensure robust and reliable data science solutions.Familiarity with big data & distributed computing frameworks such as Hadoop, Apache Spark etc.

  • Solid understanding of software and data engineering best practices.

Preferred Qualifications

  • Demonstrated competencies such as teamwork, creative problem solving, and flexibility

  • Experience with analytics restaurants and/or retail

  • A strong curiosity to continuously learn data science techniques and tools

  • Ability to work within a climate of ambiguity

  • Ability to collaborate with colleagues in multiple offices across different time zones

  • Strong personal organizational skills

  • Excellent relationship management