Data Science and Machine Learning Engineer

apartmentFeniska placeBerlin calendar_month08.01.25

Feniska is a Berlin-based startup that develops IoT products for cats, enabling data tracking of essential health metrics. Our flagship product, the Feniska Base, is a smart gadget placed under the litter box to monitor key health indicators.

The Feniska app delivers daily updates and actionable insights, helping pet owners proactively manage their cats' health.

We are seeking a Data Science and Machine Learning Engineer who is proficient in Python, experienced in machine learning, data engineering, and analytics, and has a passion for pet health technology. You should be a problem-solver who approaches challenges analytically and creatively to deliver measurable results.
Strong team collaboration skills are essential, as you'll be working closely with cross-functional teams, including product, engineering, and veterinary experts. We value adaptability to new technologies and the fast-paced demands of a growing startup.

A user-centric mindset is crucial to ensure our solutions provide real value and actionable insights to pet owners.

This role will play a pivotal part in driving innovation, refining data annotation processes, developing predictive models, and incorporating generative AI to enhance our health monitoring capabilities.

Tasks

Key Responsibilities:

Machine Learning Development:

Lead the design and implementation of machine learning models to predict health issues, using diverse datasets for comprehensive insights.

Customer Data Review and Analysis:

Perform regular review and analysis of customer data to extract insights, identify trends, and ensure data quality for improved decision-making and product refinement.

Generative AI Applications:

Develop and refine generative AI models and prompt engineering strategies to enhance user interactions, health recommendations, and automated insights.

Collaboration and Integration:

Work closely with our product team and veterinary experts to integrate predictive analytics and GenAI-based solutions into our offerings.

Feature Development:

Drive the creation of new data-driven features and capabilities, from conceptualization to deployment, ensuring impactful user experiences.

Data Annotation and Quality:

Innovate and enhance data annotation processes to improve the quality and utility of data for model training and analysis.

Requirements

Technical Skills:

Programming:

Advanced proficiency in Python and relevant data science libraries (pandas, NumPy, scikit-learn, TensorFlow, PyTorch).

Data Analysis & Engineering:

Experience extracting insights and features from large datasets, optimizing predictive model accuracy and effectiveness.

Generative AI & Prompt Engineering:

Experience building generative AI applications and crafting effective prompts for AI models to deliver accurate and contextual outputs.

Database Management:

Proficiency in noSQL databases and familiarity with SQL for data manipulation and retrieval.

Visualization:

Strong ability to use data visualization tools to communicate complex ideas clearly.

Cloud Computing:

Familiarity with AWS (or similar) for scalable data processing and machine learning model deployment.

Desirable Experience:

IoT & Biometric Data:

Prior experience working with IoT devices and health data.

Computer Vision:

Knowledge of computer vision techniques and libraries (OpenCV, TensorFlow, PyTorch) to analyze pet behaviors and health metrics.

Production Deployment:

Experience deploying machine learning models in production environments.

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