Data Science Engineer for Scalable Machine Learning Solutions
5 days ago
About the Role
We are seeking a highly skilled Data Science Engineer to join our Central Data Science team at Demandbase. As a key member of our team, you will play a pivotal role in designing and deploying scalable machine learning solutions that transform the B2B buyer's journey.
You will work closely with data scientists, product managers, and engineers to develop and operationalize machine learning models that enhance product offerings across account ranking, intent detection, and ad optimization.
The ideal candidate will have a strong proficiency in Scala, as many of our systems are built with Scala to support high-volume data processing.
Responsibilities
- Model Deployment and Optimization: Develop and deploy machine learning models that drive real-time business insights and impact campaign KPIs.
- Pipeline Development: Build robust data pipelines to support ML model training, testing, and deployment at scale, leveraging Python and Scala as core technologies.
- Cross-functional Engineering Collaboration: Work closely with data engineering, product management, and UX design teams to ensure models integrate seamlessly into our platform.
- Performance Monitoring and Tuning: Implement monitoring systems to evaluate model performance in production and develop strategies to optimize and retrain models as needed.
- Drive ML Innovation: Stay updated on industry advancements and integrate new techniques to maintain cutting-edge capabilities.
Project Highlights
- Account Intelligence: Design systems to map billions of IPs and cookies to companies for improved account ranking and personalization.
- Real-Time Intent Signals: Engineer models to trigger alerts based on real-time intent signals, enabling sales teams to act on high-value leads.
- Ad Optimization: Optimize ad performance with real-time bidding, click-through rate, and engagement models using reinforcement learning algorithms.
What We're Looking For
- Experience: 5+ years in machine learning engineering or a related field, with hands-on experience in deploying production-level models.
- Education: Degree in Computer Science, Machine Learning, Engineering, or related fields (e.g., Mathematics, Statistics, Physics).
- ML Engineering Proficiency: Demonstrated expertise in deploying and optimizing machine learning models in one or more areas:
- Ranking & Recommendation Systems
- Ad Optimization, Real-Time Bidding
- Reinforcement Learning
- Experimentation (A/B Testing)
- Technical Skills:
- Proficient in Python and ML libraries (Scikit-Learn, Pandas, Numpy, etc.)
- Experience with Scala (preferred) for data pipeline and production optimization
- Familiarity with ML frameworks like TensorFlow, Keras, PyTorch, and SparkML
- Strong SQL and No-SQL database skills
- Cloud & Data Engineering Tools: Google Cloud Platform or AWS experience preferred, along with Spark and BQML.
Salary: $160,000 - $218,000 per year
Benefits: Our benefits package includes options for up to 100% paid Medical and Vision premiums for employees, flexible PTO policy, no internal meeting Fridays, Modern Health mental wellness platform, and 11 paid holidays and 2 additional weeks where all Demandbase employees take off (the week of July 4th and the week of Thanksgiving). Plus 401(k), short-term/long-term disability, life insurance, and other perks.
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