As the Data Scientist you will be responsible to analyze large amounts of raw information and find patterns that will help improve Tempo’s continued growth. You will be called to define, analyze, report and advise on strategic operational trends across the company, while developing and maintaining durable and scalable reporting and analytical data and predictive models. You will also work closely with our Data Engineering team to ensure the integrity of the analytical and consumption layer of our data pipeline. In this role, you should be highly analytical with a knack for data wrangling, data modelling, analysis, math and statistics, while applying best practices in data mining and machine learning.
The role involves
Working with internal stakeholders to develop, execute, and test different growth experiments that have a significant impact on conversion across all funnels (attraction,, activation, acquisition, retention, referral, and monetization)
Developing advanced analytics models and deploying them seamlessly into our operations
Administering our machine learning platform, including curation and model maintenance
Being accountable for the availability and delivery of our operational and analytical data pipelines
Collaboration with the Enterprise Data Architecture team to identify new data sources, and transforming them into reusable data models
Analyze diverse sources of data to devise actionable insights
Capturing, organizing and prioritizing end user requirements and translating them into novel analytical insights
Converting insights into a story-telling format for all audiences
Developing and maintaining protocols for handling, processing, and cleaning corporate data
Helping define and maintain a durable information delivery structure and process
Participating in the continuous improvement of decision-making processes within the analytics team
Performing various tasks on a daily basis at the request of the Director of Business Intelligence
The Ideal Candidate
Has at a minimum a Master’s degree in a quantitative field, preferably in Statistics, Mathematics, Data Science or Artificial Intelligence
Has at least 5 years of professional experience in machine learning, advanced analytics, and delivering production-grade predictive models
Must have experience with a SaaS software company
Can demonstrate experience in data mining themes such as classification, regression, association rule learning, clustering/segmentation, anomaly detection, sequential pattern learning, time series forecasting, A/B testing, etc.
Must demonstrate sound knowledge and experience in providing predictive insights on digital customer journeys ranging from customer attraction to customer retention.
Demonstrated knowledge of cleansing and mining semi-structured big data, and converting them into analytic and reporting data schemas
Is experienced using Python, R, SAS, or SPSS
Has experience using data science and machine learning platforms such as Databricks, Alteryx, Microsoft Azure Synapse, GCP, AWS, H20.ai, or IBM Watson
Experience in big data repositories such as AWS S3, Google BigTable, or Microsoft Azure
Experience using analytical data warehouses such as RedShift, BigQuery, and Snowflake
Is proficient in visualizing and presenting insights using Power BI, Data Studio, Tableau, R Shiny, Plotly, or MatPlotLib
Has experience with relational SQL and NoSQL databases, including Postgres, MongoDB, BigQuery, etc.
Is intimately familiar with the CRISP-DM methodology
Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations
Can clearly communicate technical information to a non-technical audience
Can work independently and prioritize assignments to complete work in a timely manner, with minimal direction
Hitting the ground running, confidently able to draw immediate insights and make recommendations on further improving corporate performance
A proven work ethic that drives the desired results, with an excellent business acumen and excellent project management skills
Collaborating effectively with internal end-users and cross-functional teams to solve problems, implement new reporting solutions, and deliver successfully against high standards.
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