Are you passionate about applying data science to solve real-world problems and drive actionable insights?

Do you excel at turning complex data into meaningful, business-impactful solutions?

If you’re ready to build and deploy data models that make a difference, our client has the perfect role for you.

We’re seeking an Applied Data Scientist (aka The Insight Engineer) to develop and implement models that support key business functions, enhance operations, and enable data-driven strategies.As an Applied Data Scientist at our client, you’ll work closely with data engineers, product managers, and stakeholders to design and deploy predictive models that support various applications, from customer behavior analysis to operational optimization.

Your work will be integral to transforming data into tools that solve business challenges and enhance decision-making.Key Responsibilities: Develop and Deploy Predictive Models: Build and deploy machine learning models for various business applications, including customer segmentation, predictive maintenance, and churn analysis.

You’ll ensure models are production-ready and scalable.

Collaborate with Cross-Functional Teams: Partner with product managers, business analysts, and engineering teams to align model development with business objectives.

You’ll gather requirements and deliver data solutions that meet end-user needs.

Transform Data into Business Insights: Conduct exploratory data analysis to uncover trends, patterns, and actionable insights.

You’ll leverage these insights to create models that directly support business growth and efficiency.

Optimize and Maintain Models: Continuously monitor model performance and refine models based on feedback and new data.

You’ll implement retraining workflows and adjust parameters to ensure accuracy over time.

Utilize Advanced Data Techniques and Tools: Use advanced machine learning techniques, such as ensemble methods, time-series analysis, or deep learning, to solve complex business problems.

You’ll work with tools like Python, R, and TensorFlow.

Create and Present Data Visualizations and Reports: Develop visualizations and reports to communicate insights and model performance to non-technical stakeholders.

You’ll ensure that findings are accessible and meaningful for decision-makers.

Stay Updated on Industry Trends and Techniques: Keep current with the latest advancements in data science, machine learning, and AI.

You’ll integrate new techniques that can improve model accuracy, scalability, and business relevance.