Description:

The Applied Data Scientist (The Insight Engineer) role involves applying data science to solve real-world problems and drive actionable insights.
You will develop and implement models that support key business functions, enhance operations, and enable data-driven strategies.
The position requires close collaboration with data engineers, product managers, and stakeholders to design and deploy predictive models for various applications.
Key responsibilities include building and deploying machine learning models for customer segmentation, predictive maintenance, and churn analysis.
You will conduct exploratory data analysis to uncover trends and patterns, transforming data into business insights.
Continuous monitoring and optimization of model performance is essential, along with utilizing advanced data techniques and tools.
The role also involves creating and presenting data visualizations and reports to communicate insights to non-technical stakeholders.
Staying updated on industry trends and techniques is crucial for integrating new methods that improve model accuracy and business relevance.

Requirements:

Expertise in developing and implementing machine learning models, including experience with supervised and unsupervised learning techniques.
Proficiency in Python, R, or SQL for data analysis and model development, along with experience in libraries like Scikit-learn, TensorFlow, or PyTorch.
Ability to translate complex data into business insights, with an understanding of key metrics and KPIs that drive value for the organization.
Strong skills in creating data visualizations using tools like Tableau, Power BI, or Matplotlib, with the ability to present insights effectively to both technical and non-technical audiences.
Proven ability to work with cross-functional teams and approach problems with a solution-focused mindset.
A Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field is required, with equivalent experience in data science or applied analytics considered.
Certifications in data science or machine learning (e.g., AWS Certified Machine Learning – Specialty, TensorFlow Developer Certificate) are advantageous.
A minimum of 3 years of experience in data science or machine learning, with a proven record of applying models to solve business challenges.
Experience deploying models in production environments, ideally with cloud-based platforms (AWS, GCP, Azure), is required.
A background in a specific industry, such as finance, healthcare, or marketing analytics, is beneficial but not required.

Comprehensive medical, dental, and vision insurance plans with low co-pays and premiums are provided.
Competitive vacation, sick leave, and 20 paid holidays per year are included in the paid time off policy.
Flexible work schedules and telecommuting options promote work-life balance.
Opportunities for training, certification reimbursement, and career advancement programs support professional development.
Access to wellness programs, including gym memberships, health screenings, and mental health resources, is available.
Life insurance and short-term/long-term disability coverage are part of the life and disability insurance benefits.
Confidential counseling and support services for personal and professional challenges are offered through the Employee Assistance Program (EAP).
Financial assistance for continuing education and professional development is provided through tuition reimbursement.
Opportunities to participate in community service and volunteer activities are encouraged for community engagement.
Employee recognition programs celebrate achievements and milestones within the organization.