Data Scientist (Marketing and Natural Language Processing)

Primary objective:

  • Data Scientist will be responsible for applying data science and advanced quantitative methods, which include machine learning, deep learning, artificial intelligence, predictive analytics to enable strategic use cases, key operational and tactical skills in marketing, communications and strategy. , and natural language processing – in accordance with the internal digital strategic framework. Responsible for the end-to-end data lifecycle – from strategic planning to data collection, monitoring, evaluation and incremental improvement.
  • Reporting to: Chief Digital Officer

In this role, you will enhance the current and future analytics environment and data platforms, and associated data products and services for consumption.
In addition, the focus will include identifying key organizational problem statements, opportunities, user data experience and journey requirements, through data collection and use of a wide range of statistical, machine learning and applied mathematics techniques to provide predictive insights and analytics for decision making. -manufacturers. In addition, you will provide technical advice and support to senior data teams and municipal decision makers in the area of ​​marketing, communication, strategy and natural language processing.

Specific job requirements

  • Bachelor’s or Honors degree in Statistics, Mathematics, Applied Mathematics, Physics, Econometrics, Actuarial Science or equivalent experience
  • Master in Statistics, Mathematics, Applied Mathematics, Physics, Econometrics, an asset
  • 3+ years of experience in data science and analytics
  • Proficiency in Python and database technologies


1) Data pre-processing and transformation

  • 35%
  • Demonstrate ability to transform raw data from multiple data sources. – Ability to understand business requirements specifications and use suggested model to transform data. – Ability to understand differences between data types and transform data types where necessary. – Ability to write ETL jobs and automate pipelines if necessary. – Ability to investigate anomalies when loading data into the required data source – Ability to find external data sources to use in machine learning processes. – Ability to work and know what tools of platform to use for data transformation.- Explore data for patterns and trends,- Ability to translate and reproduce mock-ups design of data analytics dashboards

2) Build and Deployment Modeling

  • 35%
  • Demonstrate ability to translate business use cases into machine learning problems. Understand the end-to-end process of building a machine learning model, including data transformations, splitting training tests, saving, and deploying machine learning models. Assist the Senior Data Scientist in deploying machine learning models in production. Monitor and debug machine learning pipelines in production. – Ability to work and know which platform tools to use for machine learning and deployment.

3) Strategic support

  • 15%
  • Support senior management and city communications teams to plan and execute agreed performance agreement goals for career development- Manage team of data scientists to deliver all strategic and analytical outputs as required- Work with team members when necessary to achieve data science team goals – Provide project support on domain-specific projects – Provide feedback to senior management on work and progress deliverables – Write evaluation reports to include the performance of algorithms used for machine learning use cases- Identify data science innovation that creates an ownership advantage for the business- Work with senior data scientist to identify specific data science roles to specialize in the data science team e of data- Proactively develop data products for emerging use cases- Provide guidance and support to municipal data teams.

4) Behavioral skills

  • 15%
  • Demonstrate ability to develop and maintain personal and working relationships with others that facilitate work completion, exchange of information, and to foster and promote peak performance and overall organizational effectiveness- Demonstrate ability to research and document the latest applications of data science pipeline best practices – Demonstrate ability to perform high quality work without supervision – Demonstrate ability to work, adapt and contribute to process changes within of the team


  • Support the Digital Director and Senior Data Architect using a variety of leading cloud-based technologies to solve data analytics and prediction issues.
  • Identify and act on new opportunities for data-driven businesses in data science and analytics.
  • Recognize when existing solutions can be generalized to solve new problems and address new data-as-a-service verticals
  • Work in a collaborative environment developing data science methods, tools and algorithms to solve problems.
  • Master analytical modeling using in-house data modeling platforms and tools
  • Continuously learn and apply the latest and most relevant, open-source and proprietary tools and technologies to achieve results, including some or all of the following:

  • Cloud:

  • Microsoft Azure (required)
  • AWS
  • Google Cloud

  • BigData:

  • Mondodb
  • Hadoopo Cassandra

  • Machine learning:

  • KubeflowName
  • Tensor flow
  • TorchPy

  • Business Intelligence/Analytics and visualization:

  • Microsoft PowerBi (required)
  • Microsoft Excel (required)
  • Google Analytics (required)
  • Adobe Analytics (required)
  • Google Chartso NLTK (required)
  • Textblobo SpaCy
  • CoreNLP
  • Datorama (advantage)

  • Languages ​​:

  • Python (required)
  • R (must)
  • SQL (required)

  • Conversational AI:

  • Dialog flow
  • Teneo
  • Bot Framework / Bot Builder SDK (ideal)
  • Watson-Wizard

  • Related tools and technologies as they become available and the platform evolves – Load and merge data from various sources.

  • Performa Data Cleansing and Quality Management
  • Preprocess and transform data for model building and analysis
  • Troubleshoot data quality issues and work with team members to find solutions – Perform descriptive analysis to uncover trends and patterns in data;
  • Create visualizations including dashboards to provide insights into large datasets and inputs into finished reports
  • Develop predictive models for business solutions.
  • Deploy predictive and other models in production.
  • Build and train NLP models
  • Analyze output products to ensure data quality and compliance with requirements.
  • Develop technical specifications for third-party platform data integration and streaming
  • Participate in continuous improvement efforts to increase the quality of data available and the speed of delivery
  • Respond to ad hoc domain-specific data analysis requirements of domain or cluster managers; and continuously provide user-centric data visualizations, publications and products

Skills/Abilities Required to Do the Job:

  • Ability to develop embedded machine learning tools using python, R
    • Ability to manage structured and unstructured data using SQL
    • Ability to visualize data using various tools – Ability to create conversational AI (artificial intelligence) models
    • Ability to model data for prediction
    • Ability to manage project time and deliverables
    • Ability to communicate with executives and senior management from all sectors (local government, government and industry)
    • Basic understanding of marketing and communications management processes

Desired skills:

  • Python
  • database technology
  • SQL
  • artificial intelligence
  • ETL
  • Sentiment analysis
  • – Stemming and lemmatization
  • Keyword extraction
  • Topic Modeling
  • Text mining
  • Named entity recognition
  • machine learning
  • deep learning
  • Programming
  • Data analysis
  • Database configuration and management
  • Data visualization
  • Predictive analytics
  • Business acumen
  • Agile

Desired work experience:

  • 2 to 5 years Data Analysis / Data Warehousing

Desired level of qualification:

Find out more/Apply to this position

Sean N. Ayres