Senior Data Scientist, Machine Learning

Key Skills

Apache Airflow, AWS, AWS Kinesis, Cloudflare, DynamoDB, Kubernetes-K8s, Pandas, Postgres, PyTorch, REDIS, TensorFlow, Terraform, UI design

Job Description

About Attentive:

Attentive® is the leader in conversational commerce, reinventing business to consumer communication. Our SMS-first software platform helps everyone from entrepreneurs to enterprises strengthen relationships with their consumers in a new way. Through two-way, real-time, personalized communications, we drive billions in e-commerce revenue and over 8,000 leading brands like CB2, Urban Outfitters, Crocs, Jack in the Box, and Coach rely on Attentive to deliver powerful commerce experiences.

Attentive’s growth has been recognized by Deloitte’s Fast 500, Linkedin’s Top Startups and Forbes Cloud 100 all thanks to the hard work from our global employees!

Who we are

Our engineering department consists of 200+ people across multiple teams, such as application development, infrastructure, data platform, data science and machine learning, and security. We believe our company will win in the long run through product innovation. To get there, we obsess over iteratively delivering customer value through rapid prototyping and data-driven decision-making.

As a Senior Data Scientist working on our AI portfolio, you will be a pivotal contributor, transforming data into actionable insights. Your work will guide the development of software solutions that enable our marketing team to craft high-performing messages.

Why Attentive needs you:

• Develop data-driven strategies to address key business challenges, such as customer segmentation, churn prediction, and lifetime value optimization.
• Use advanced statistical methods and machine learning techniques to analyze and interpret complex data, transforming it into insights that can guide decision-making for both our product and marketing teams.
• Partner with product managers to translate business needs into data analysis projects, helping to define KPIs and interpret the results to make actionable recommendations.
• Provide guidance on the proper implementation of data science models within our existing software environment, ensuring models are interpretable, robust, and aligned with business objectives.
• Collaborate with data engineers and machine learning engineers to develop scalable and reliable data pipelines for model training and inference.
• Implement frameworks for monitoring the performance and validity of analytics and machine learning models, ensuring their continued relevance and accuracy.

About you:

• At least 5 years of professional experience as a Data Scientist, with a specialized focus on software development and advanced analytics.
• A proven track record of designing, developing, and deploying software solutions powered by machine learning and data analytics.
• Strong expertise in Python, along with proficiency in data manipulation libraries like Pandas and modeling and analysis tools such as NumPy, Scikit-learn, XGBoost, Matplotlib, Seaborn, Scipy.
• Demonstrable skill in SQL and experience with database systems like PostgreSQL or MySQL.
• Expertise in working with large data sets using distributed computing platforms such as Hadoop, Spark, or AWS services like EMR and S3.

Our scale

• 8,000 brands powered by Attentive sent over 1.6 billion text messages over Cyber Week 2022 (Black Friday/Cyber Monday) representing a growth of 41% from 2021
• We sent 24 billion SMS messages in 2022. That’s an average of 50 million per day
• Our production cluster contains over 9,000 containers which serve 170+ services
• Our streaming services process over 28 billion events per month

What we use

• Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS
• Infrastructure tooling includes Istio, Datadog, Terraform, CloudFlare, and Helm
• Our backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, Kinesis, AirFlow, Postgres, Planetscale, and Redis, hosted via AWS.
• Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and Playwright
• Our automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace