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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 excellent 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.

Job Description
  • Design, develop, and deliver statistical and predictive models for the client and internal projects.
  • Work with the multi-functional team consisting of business stakeholders, engineering, and IT teams and designers to deliver scalable projects.
  • Identify and drive new and innovative use cases for the data-driven product for both clients and internal stakeholders.
  • Analyze and validate new or improved models via statistically relevant experiments and A/B testing.
  • 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 regularly.
  • Provide support in identifying opportunities in creating customer value with AI.
  • Mentor AI Interns 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/Ph.D. preferred) in an analytical subject, e.g., data science, engineering, economics, business, statistics, mathematics or related fields.
  • +2 years of hands-on experience in a relevant field of data science, preferably in real industry settings, and have build 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.
  • Proficient in using query languages such as SQL as well as good scripting and programming skills.
  • Some Big Data experience with Apache Spark and Kafka. Cloud ML platforms like AWS Sagemaker and GCP ML Engine 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 in high-pressure situations.