Job Description

Data Axle Inc. has been an industry leader in data, marketing solutions, sales and research for over 45 years in the US. Data Axle is now setting up a strategic global centre of excellence in Pune. This centre will deliver mission critical data services to its global customers powered by its proprietary cloud-based technology platform and leveraging proprietary business & consumer databases. Data Axle is headquartered in Dallas, TX, USA.

Data Axle Pune is pleased to have achieved certification as a Great Place to Work!

Roles & Responsibilities:

We are looking for a Data Scientist to join the Data Science team to continue our success of identifying high quality target audiences that generate profitable marketing return for our clients. We are looking for experienced data science, machine learning and MLOps practitioners to design, build and deploy impactful predictive marketing solutions that serve a wide range of verticals and clients. The right candidate will enjoy contributing to and learning from a highly talented team and working on a variety of projects.

We are looking for a Manger Data Scientist who will be responsible for

• Ownership of design, implementation, and deployment of machine learning algorithms in a modern Python-based cloud architecture
• Design or enhance ML workflows for data ingestion, model design, model inference and scoring
• Oversight on team project execution and delivery
• Establish peer review guidelines for high quality coding to help develop junior team members’ skill set growth, cross-training, and team efficiencies
• Visualize and publish model performance results and insights to internal and external audiences

Qualifications

1. Masters in a relevant quantitative, applied field (Statistics, Econometrics, Computer Science, Mathematics, Engineering)
2. Minimum of 9+ years of work experience in the end-to-end lifecycle of ML model development and deployment into production within a cloud infrastructure (Databricks is highly preferred)
3. Proven ability to manage the output of a small team in a fast-paced environment and to lead by example in the fulfilment of client requests
4. Exhibit deep knowledge of core mathematical principles relating to data science and machine learning (ML Theory + Best Practices, Feature Engineering and Selection, Supervised and Unsupervised ML, A/B Testing, etc)
5. Proficiency in Python and SQL required; PySpark/Spark experience a plus
6. Ability to conduct a productive peer review and proper code structure in Github
7. Proven experience developing, testing, and deploying various ML algorithms (neural networks, XGBoost, Bayes, and the like)
8. Working knowledge of modern CI/CD methods