Data Scientist at Cellulant Corporation

Responsibilities for the Data Scientist Job

• You will use your ability to create value-adding analytic systems, toolsets and processes that support user acquisition, user engagement, usage growth and retention.
• Work in a multi-disciplined team where you’ll take full ownership of turning discoveries and ideas into machine learning models. You’ll use the model’s output to help us create and improve products and features for our customers, preferably in short cycles.
• Our ideal candidate is result-focused, innovative and has solid quantitative background and a good business understanding.
• Ability to Transform large, complex datasets into pragmatic, actionable insights and in turn quantify and influence tangible business gain.
• Ability to see beyond the numbers, be the voice of data when communicating to decision makers, product owners and other business leaders.
• Create insightful data visualizations that highlight trends.
• Sourcing and implementing data gathering processes from multiple sources including product usage records, VOC and customer databases to create integrated views and insights that can be used to drive decision making.
• Preparing periodic, continuous and ad hoc reports clearly showing business trends and customer behavior.
• Track consumer behavior on daily and weekly trackers as well as on weekly, monthly/quarterly and yearly reports.
• Monitor product lifecycle and highlight early signs of product use change.

Qualifications for the Data Scientist Job

• Bachelor’s Degree in Statistics, Actuarial Science, Computer Science or Economics. Must show experience in data analysis.
• 4 or more years’ experience in a reporting/data analysis role(s) and environments. Experience in using SQL based data mining and analysis required. Experience with NoSQL databases, such as MongoDB, Cassandra, HBase an added plus.
• Experience with common data science toolkits, such as R, Weka, NumPy, MatLab, etc Excellence in at least one of these is highly desirable.
• A good scripter able to use analysis tools creatively to programmatically answer complex business questions in a data driven approach at relative speed.
• Good applied statistics skills and experience, such as distributions, statistical testing, regression, etc. with excellent understanding of machine learning techniques and algorithms, such as k-means, Naive Bayes, SVM and Decision Trees.
• Experience in building and/or maintaining an ETL data flow system an added plus though not a must. The candidate must however demonstrate that he/she has a good understanding of data cleaning and transformation techniques.
• Strong co-ordination and project management skills to handle complex projects.
• Entrepreneurial, Positive, people-oriented, and energetic attitude.
• Ability to manage a large queue of work and meet assignment deadlines through personal initiatives on several simultaneously assigned tasks.