Senior Data Scientist

The Senior Data Scientist will leverage advanced academic qualifications and extensive applied knowledge to derive significant value from data science efforts. This role will have the autonomy and ownership to rapidly create impactful data solutions, taking on leadership roles to manage complex projects and provide strategic guidance that elevates the team’s capabilities. Working both independently and within cross-functional teams, the Senior Data Scientist will develop and deploy actionable insights that guide strategic decisions, leading to better resource allocation, improved engagement, and more effective business strategies.

The broad and deep background in data science, including specializations such as natural language processing (NLP), deep learning, and forecasting, will enable this role to translate business problems into data problems, lead solution development with machine learning or broader AI techniques, and convert insights into recommendations and value. The Senior Data Scientist will encompass a product mindset that will drive the development and adoption of innovative solutions, helping the team establish technical specialization and expertise in response to the continued evolution of the data science field.

What you'll do:

• Leads complex projects, designing, developing, and deploying advanced machine learning models using diverse data to inform strategic decisions, marketing, and advertising strategies, driving business outcomes
• Provides strategic guidance, translating business challenges into data solutions, managing development and delivery, and supporting planning, resource availability, and stakeholder engagement
• Mentors junior team members, supports their growth, and collaborates on downstream steps, including code refactoring, testing, deployment, monitoring, and integration
• Queries, analyzes, and models diverse datasets, including GA4 data, to develop predictive models and automate dataset generation and insights with support from partner teams
• Develops proficiency and utilizes both Google Cloud Platform (GCP) and Microsoft Azure, leveraging tools such as BigQuery, BigQuery ML, Colab Enterprise, Looker, Vertex AI, Cloud Source Repositories, Azure Machine Learning, Fabric, Azure Data Factory, and Azure Repos. Develops and deploys solutions using SQL and Python
• Communicates project status through agile ceremonies, shares insights with stakeholders, develops structured repositories, and operates in an agile environment, utilizing estimation, adaptability, and continual delivery
• Supports the development of planning and estimates for associated scope, ensuring the availability of relevant resources (e.g., datasets and tools). Engages in stakeholder and change management to support the effective use of solutions
• Automates the generation of datasets and insights by deploying data and model pipelines, with support from partner teams, including Data Engineering
• Revises the dataset construction process through iterative development, incorporating feedback and quality assurance (QA) measures to ensure accurate and reliable results
• Explores and remains curious about new areas in data science and AI fields. Conducts research and develops expertise in these areas as relevant to projects, especially through practical application. Maintains a focus on continual improvement

What you'll need:

• Proficiency in SQL and Python for data manipulation, analysis, and model development, with advanced knowledge of databases and data representation
• High degree of knowledge in platforms, such as Google Cloud Platform (GCP), Microsoft Azure, or AWS
• Strong analytical and problem-solving skills, with strategic thinking and business acumen to translate business challenges into data solutions and align them with industry trends and business objectives
• Excellent communication and data visualization skills, with the ability to present complex data insights clearly and effectively to non-technical stakeholders
• Curiosity, continuous learning, and adaptability, with a focus on staying updated with the latest advancements in data science and AI and applying new knowledge to projects
• Exhibits ownership, candor, and conscientiousness in their work
• Demonstrates diligence when analyzing data and building models to ensure accuracy and reliability
• Leadership and mentoring skills, with strong people skills to foster collaboration and effective communication within cross-functional teams
• Proficiency in advanced statistical analysis, including regression analysis, time series analysis, and hypothesis testing<