Senior Data Scientist

Lightspeed is seeking an experienced and highly skilled Senior Data Scientist to join our growing team. As a Senior Data Scientist, you will play a crucial role in leveraging data-driven insights to enhance our business strategies, drive innovation, and optimize decision-making processes. Sitting on our newly established Data Science Enablement team, you will focus on building predictive and prescriptive models to solve a range of problems across various business units, and establishing data science best-practice for the company. You will collaborate with cross-functional teams to deliver actionable solutions that drive our organization's growth and success.

What you’ll be responsible for:

Data Analysis and Modeling:

1. Conduct extensive data analysis using statistical and machine learning techniques to identify patterns, trends, and relationships within datasets.
2. Develop predictive and prescriptive models to forecast market trends, fraud, delinquency, customer behavior, and optimize the performance of critical business metrics.
3. Utilize various data sources and data preprocessing techniques to ensure data quality and integrity.

Machine Learning and AI Solutions:

1. Design, develop, implement and maintain cutting-edge machine learning algorithms and AI solutions for use-cases that have high impact on the business.
2. Take ownership of migrating ML models from development to production environments.
3. Collaborate closely with engineering teams to ensure smooth deployment, scaling, and integration of models in real-time or batch systems.

Business Strategy and Insights:

1. Collaborate with business leaders to understand their challenges and goals, providing data-driven insights and recommendations that drive strategic decision-making.
2. Identify opportunities to leverage data to improve product offerings, customer experience, and operational efficiency.
3. Deliver machine learning models for use-cases that have a high impact on real-world business applications.

Model Validation and Performance Monitoring:

1. Validate and assess the performance of deployed models regularly, ensuring their accuracy, stability, and effectiveness over time.
2. Implement monitoring systems to track model performance and detect deviations, providing timely feedback to maintain model integrity.

Data Visualization and Communication:

1. Act as a champion for a data-driven culture, promoting data literacy across the organization and empowering teams with the skills and knowledge to leverage data.
2. Create clear and concise data visualizations and reports to communicate complex findings to both technical and non-technical stakeholders.
3. Translate analytical results into actionable business insights and present findings to senior management in a compelling and easily understandable manner.

Technical Leadership:

1. Provide guidance and mentorship to junior data scientists and other technical team members, fostering the development of best practices.
2. Champion the exploration of new technologies, tools, and methodologies in data science, ensuring the team drives technical innovation that aligns with business goals.

Skills and Qualifications:

1. Master's or Ph.D. in a quantitative field such as Data Science, Statistics, Computer Science, Engineering, or Mathematics.
2. Proven experience as a Data Scientist, preferably in the financial services sector with credit risk modeling experience, with a track record of successful project delivery and business impact.
3. Expertise in Python & SQL and expertise in data manipulation, analysis, and machine learning using libraries like NumPy, Pandas, and scikit-learn.
4. Solid understanding and practical experience with machine learning algorithms, statistical modeling, and data mining techniques (bonus points for experience with ML engineering and/or operations in a production setting).
5. Familiarity with cloud platforms (we are using GCP) for scalable data processing and analysis, as well as for machine learning model development and deployment.
6. Strong knowledge of databases and SQL for data retrieval and manipulation.
7. Experience with data visualization tools like Looker, Tableau or Power BI to create insightful reports and dashboards.
8. Excellent problem-solving skills, analytical thinking, and the ability to thrive in a fast-paced, results-oriented environment.
9. Effective communication and presentation skills, with the ability to communicate complex technical concepts to non-technical audiences.