Machine Learning Engineer
At Leapfrog, our mission is to be a role model technology company. We want to be trusted partners, world-class engineers, and creative innovators for our clients. We have built awesome software that puts data into action. Our team specializes in data-driven digital products that help businesses transform and capture new markets.
We are looking for a Data Scientist to join our AI team. This position offers you an excellent opportunity to work with real-world Data Science and Machine Learning systems.
- Design, develop, and deliver statistical and predictive models for the client and internal projects.
- Work with a multi-functional team consisting of business stakeholders, engineering, and IT teams, designers, etc. to deliver scalable projects.
- Identify and drive new and innovative use cases for data-driven products for both clients and internal stakeholders.
- Analyze and validate new or improved models via statistically relevant experiments and A/B testing.
- Setup and measure Product Analytics KPIs for our client apps and products.
- Leverage software engineering and design best practices.
- Work closely with other team members to build scalable prototypes for testing, and integrate successful models and algorithms in production systems.
- Communicate the results of data exploration, analysis, and ML models to both technical and non-technical stakeholders on a regular basis.
- Support in identifying opportunities in creating customer value with AI.
- Mentor junior team members and evangelize best practices to other team members.
- Propose and document best practices/standards for the design, development, evaluation, and deployment of Data Science projects
- A degree ( Master’s/PhD preferred) in an analytical subject, e.g. data science, engineering, economics, business, statistics, mathematics or related fields.
- Minimum 2+ years hands-on experience in a relevant field of data science, preferably in real industry settings, and have built data products that have impacted customer and revenue growth.
- Good understanding of machine learning techniques and algorithms.
- Ability to apply appropriate advanced analytics techniques such as Bayesian, statistics, clustering, text analysis, time series methods, and neural networks on large-scale datasets.
- Highly experienced in creating production-quality code in Python and some experience deploying code web frameworks like Flask.
- Well versed with the Python data ecosystem (Numpy, Scipy, Pandas, Scikit-Learn, Tensorflow or PyTorch), or equivalent in R, Java, Scala, Julia etc.
- Proficiency in using query languages such as SQL as well as good scripting and programming skills, especially in the context of analytics platforms/data warehouses is preferred.
- Experience working on a cloud environment like AWS, Azure, or GCP for ML work.
- Some Big Data experience with Apache Spark, Kafka etc. and cloud ML platforms like AWS Sagemaker, GCP ML Engine etc is a bonus.
- Any experience with data visualization and dashboard tools like Tableau, Power BI etc. is a bonus.
- Our work requires you to be highly motivated and must be capable of working in a self-driven, entrepreneurial environment. We expect you to be a strong self-learner and able to solve complex analytical problems under high-pressure situations.