Data Scientist

At Lantern , our company culture stands as the bedrock of our success and a source of pride for our teams. We firmly believe that a culture founded on trust forms the basis for enduring relationships with clients, colleagues, and partners.

Within this culture, we nurture an environment of respect, inclusion, and belonging, fostering collaboration among inspired teams. We prioritize the well-being of our colleagues, the success of our clients, and our positive impact on society.

Embracing a growth mindset where curiosity thrives, we celebrate excellence and value individuals who inspire and mentor others, elevating the collective. Our driving force lies in personal and business growth. We go above and beyond to surprise and delight our clients, delivering tangible business value. In facing challenges, we make tough choices and solve complex problems to positively influence our clients, their customers, and the world at large.

As a Microsoft services partner, we hold ourselves to the highest standards of technical excellence. This commitment to quality is evident not only in our work but also in how we support and empower our employees. At Lantern, our culture mirrors our core values and unwavering dedication to realizing our purpose and vision, making it a dynamic and fulfilling workplace. Together, we transcend the ordinary and achieve extraordinary results.

As a Data Scientist , you will be responsible for assisting our clients envision, design, develop, and deploy machine learning solutions in Microsoft Azure. As part of a small, dynamic team, you will have the opportunity to contribute to multiple projects and multiple phases of the solution life cycle including solution design and implementation.

Key Responsibilities

• Experience in the full ML lifecycle - understanding, developing, deploying, and maintaining traditional data science solutions.
• Proficiency with Microsoft Azure technologies such as Azure Machine Learning and Azure Databricks.
• Strong programming skills in Python or PySpark.
• Solid understanding of supervised + unsupervised learning algorithms and concepts.
• Experience with data preparation, feature engineering, and data engineering practices. Understanding of supervised + unsupervised learning algorithms and concepts.
• Experience in the optimization and tuning of machine learning solutions to handle large volumes of data.
• Outstanding verbal and written communication skills.
• Excellent presentation and whiteboarding skills.
• Experience communicating highly technical concepts to non-technical audiences.
• Experience collaborating with business stakeholders to understand business requirements and design AI solutions which meet those requirements.

Skills, Knowledge and Expertise