Machine Learning Scientist

Job title: Machine Learning Scientist

Company: Dig Insights

Job description: Dig Insights is a tech-enabled research company that helps our clients – global consumer brands – move beyond consumer-centric to decision-centric. Our clients can then go-to-market with innovations that shift consumer decisions in their favor.Our work is supported by the technologies that we leverage and create. This includes Upsiide, our proprietary innovation insights platform. Upsiide is a SaaS platform that reinvents how enterprise companies screen, optimize, and build a business case for innovation.Our clients span verticals including CPG, QSR, retail, technology, financial services, and telecommunications. Our work is led by a team of over 250 strategists, insights leaders and data scientists. We work for a global client base out of offices in Toronto, Chicago, and London.Our success is due to our strong commitment to our clients, and the creativity and dedication of our entire team. Since the beginning, we have been focused on building the smartest consumer insights company and that means hiring people who are bright, creative, resourceful, and kind. People who succeed at Dig are curious, question established norms and are passionate about helping our clients to move their businesses forward. If you want to join a team that takes themselves just seriously enough to produce great work, we’d love to welcome you.As we continue to grow, both geographically and in our expertise we are looking for people who want to join a high-growth and highly collaborative company.Machine Learning Scientist – About this roleWe are seeking a talented and proactive Machine Learning Scientist to join our AI team. The successful candidate will play a critical role in developing and refining predictive models, conducting data mining, and creating visualizations that drive insights and decision-making for our clients.Your primary responsibilities will include, but are not limited to:

• Predictive Modeling:

• Develop and refine predictive models.
• Evaluate and interpret model performance
• Compare models on a variety of metrics
• Collaborate with cross-functional teams to implement and optimize model architecture.
• Data Mining and Thematic Analysis:

• Standardize thematic analysis (identifying key themes in successful ideas and products) and help productization.
• Utilize data mining techniques to uncover insights across different demographics, categories, and industries.
• Develop general learnings and recommendations based on data analysis, such as trends in product performance across different markets.
• Visualizations and Reporting:

• Present data-driven insights through clear and effective visualizations. E.g., Creating relevant and compelling visualizations to compare performance across various categories, industries, and geographies.
• Develop large-scale product visualizations.
• Contribute to creating norms.
• Platform Integration and Automation:

• Work closely with the tech team to integrate scripts and analyses into Upsiide platform/features.
• Provide consultation and collaborate with tech team on process improvements to facilitate downstream analyses and other automation needs within the platform.
• Continuous Learning and Process Improvement:

• Stay updated with the latest advancements in machine learning and AI technologies.
• Actively engage with the team to enhance existing methodologies and develop new approaches to data analysis and model development.
• Proactively explore novel applications of machine learning and AI techniques to existing data to provide value/insights to customers.

Experience, Skills and Requirements:

• Education: Master’s or PhD in Data Science, Machine Learning, Artificial Intelligence, or a related field.
• Experience: 2-3 years of hands-on experience with machine learning in Python.
• Technical Skills:

• Proficiency in Python and machine learning libraries such as TensorFlow, PyTorch, and scikit-learn.
• Strong data analysis skills with SQL experience.
• Strong data visualization skills and experience with packages like Matplotlib or Seaborn.
• Experience with finding insights in large datasets.
• Experience productionalizing machine learning models is an asset.
• Familiarity with cloud platforms (AWS, Azure) and R is a plus.
• Soft Skills:

• Strong analytical and problem-solving abilities.
• Excellent communication skills, with the ability to convey complex technical concepts to both technical and non-technical stakeholders.
• Proactive and self-motivated, with the ability to work independently and to learn and adapt quickly to new challenges.

Work Perks:

• A hybrid-remote work environment, where employees have the flexibility to work remotely or from one of our offices
• Unlimited vacation policy
• Reimbursement for health and wellness classes/memberships and continuous learning
• RRSP / 401K employer matching program
• Offices in Toronto and Chicago, located steps to public transportation in the downtown core
• Regular social events such as charity poker nights, trivia events, team building days, and more!

To find out more about us visit us at &Our culture is built on 5 core values: Energy, Excellence, Evolution, Equality and Empathy. We believe that our success is dependent on the diverse talents, skills, and ideas of its staff. We are committed to creating an inclusive work environment and encourage applications from all qualified candidates including those in the BIPOC and LGTBQ communities, and from people with disabilities.We thank you for your interest in Dig Insights, however, only candidates who are chosen for an interview will be contacted.

Expected salary:

Location: Toronto, ON

Job date: Sun, 25 Aug 2024 01:32:55 GMT

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