RevX helps app businesses acquire and reengage users via programmatic to retain, monetize, and accelerate revenue. We're all about taking your app businesses to a new growth level. We rely on data science, innovative technology, and AI, and a skilled team, to create and deliver seamless ad experiences to delight your app users.

That’s why RevX is the ideal partner for app marketers that demand trustworthy insights, a hands-on team, and a commitment to growth.

We help you build sound mobile strategies, combining programmatic UA, app re engagement, and performance branding to drive real and verifiable results so you can scale your business: with real users, high retention, and incremental revenue.

Position description

We are seeking a talented and motivated Data Scientist with 3-6 years of experience to join our Data Science team. If you have a strong passion for data science, expertise in machine learning, and experience working with large-scale datasets, we want to hear from you.

As a Data Scientist at RevX, you will play a crucial role in developing and implementing machine learning models to drive business impact. You will work closely with teams across data science, engineering, product, and campaign management to build predictive models, optimize algorithms, and deliver actionable insights.

Your work will directly influence business strategy, product development, and campaign optimization.

Major Responsibilities

Develop and implement machine learning models, particularly neural networks, decision trees, random forests, and XGBoost, to solve complex business problems.
Work on deep learning models and other advanced techniques to enhance predictive accuracy and model performance.
Analyze and interpret large, complex datasets using Python, SQL, and big data technologies to derive meaningful insights.
Collaborate with cross-functional teams to design, build, and deploy end-to-end data science solutions, including data pipelines and model deployment frameworks.
Utilize advanced statistical techniques and machine learning methodologies to optimize business strategies and outcomes.
Evaluate and improve model performance, calibration, and deployment strategies for real-time applications.
Perform clustering, segmentation, and other unsupervised learning techniques to discover patterns in large datasets.
Conduct A/B testing and other experimental designs to validate model performance and business strategies.
Create and maintain data visualizations and dashboards using tools such as matplotlib, seaborn, Grafana, and Looker to communicate findings.
Provide technical expertise in handling big data, data warehousing, and cloud-based platforms like Google Cloud Platform (GCP).

Required Experience/Skills

Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
3-6 years of experience in data science or machine learning roles.
Strong proficiency in Python for machine learning, data analysis, and deep learning applications.
Experience in developing, deploying, and monitoring machine learning models, particularly neural networks, and other advanced algorithms.
Expertise in handling big data technologies, with experience in tools such as BigQuery and cloud platforms (GCP preferred).
Advanced SQL skills for data querying and manipulation from large datasets.
Experience in data visualization tools like matplotlib, seaborn, Grafana, and Looker.
Strong understanding of A/B testing, statistical tests, experimental design, and methodologies.
Experience in clustering, segmentation, and other unsupervised learning techniques.
Strong problem-solving skills and the ability to work with complex datasets and machine learning pipelines.
Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.