Full Stack Data Scientist

Here, we value you as a whole person. We care about the skillset you bring to the table, but more importantly, we care about the kind of person you are, and the culture and attitude you bring to the table. As a Senior Full Stack Data Scientist, you will build data products that will affect thousands of customers with the objective to improve user experience, drive revenue and optimize processes. You will find success in this role if you are a seasoned data scientist who enjoys to design, build and implement statistical models, covering the whole process end-to-end from idea to production., + Solve new and challenging problems around eCommerce payments, credit issuance and settlement, fraud detection, SaaS integration, model serving

• Work cross-functionally with some of the best people in different disciplines like data science, analytics, finance, product management, marketing & sales, design
• Break down business problems into statistical and machine learning problem formulations
• Explore, identify, query and correlate data from several different state-of-the-art data sources (Snowflake, Databricks Delta, Redis, etc.)
• Use advanced statistical methods to identify meaningful patterns, producing insights from data
• Develop robust classification, function approximation and anomaly detection models based on relational, text, image and time series data
• Use feature engineering to extract the best signals for a problem and apply suitable regularization techniques
• Develop and write production grade code in Python for our back-end microservices and REST APIs that serve our machine learning applications
• Drive quality by writing unit, integration, and performance tests in a continuous delivery environment

• You are a seasoned and versatile data scientist, who is passionate about your work
• You have a strong sense of ownership and accountability
• You are proactive and adaptable
• You like to solve problems and to fill in the gaps where there are unknowns
• You are a craftsman in your trade but you understand when "good enough" is enough
• You are analytical and have keen attention to details
• You have your own opinions and you are not shy about them, but you also value consensus and strive to achieve it
• You lead your teammates by example, you're the "go to" individual
• You're not afraid to change your mind given new facts, nor are you afraid to admit your mistakes
• You thrive in a semi-structured start-up environment with ample opportunity and also plenty of ambiguity
• You can wear multiple hats
• You have excellent communication skills and are able to explain your ideas clearly and concisely and enjoy sharing them
• You are very serious about the quality of your work and you ask no less from your colleagues
• You understand and are interested in both big picture and nitty-gritty details, + 6+ years industry experience
• Very good understanding of applied statistics, such as distributions, hypothesis testing, regression, classification, etc.
• Excellent understanding of machine learning techniques and algorithms, such as k-means, k-NN, naive Bayes, SVM, tree-based models, HMM, neural nets, deep learning etc.
• Thorough, expert level knowledge of data structures, algorithms, object oriented programming and design patterns in Python
• Deep understanding and experience of various technologies, frameworks and libraries in the Python ecosystem
• Strong familiarity with *nix environment including bash and command-line tools
• Experience with Git version-control system
• Strong experience with relational and non relational databases, including SQL
• Familiarity of web service technologies and REST best-practices
• Basic understanding of distributed systems in a cloud environment, and event-driven architecture
• Bachelors or Masters degree in Computer Science, a related field or equivalent experience
• Strong interpersonal and communication skills are required
• Excellent command of the English language, both written and spoken is a must for communicating with a global team
• Proven track record of shipping models in a delivery-focused environment
• Exposure to Amazon Web Services
• Prior startup experience a big plus