Job Description

Job Responsibilities :

- Understand client's business needs, and design solutions to address the same

- Evaluate different statistical, machine learning, and data science techniques to identify the ones that delivers maximum value to clients at a reasonable effort

- Identify data requirements for solving business problems, and use appropriate packages and tools to build predictive and prescriptive model that deliver actionable insights

- Lead client and project engagements and ensure that timelines and deliverables are being met or bettered (Travel may be required)

- Develop and implement analytical / statistical methodologies, and learn and apply new statistical analysis and big data tools

- Provide thought leadership and solutions, but not limited to: Fraud Detection, Yield Management, Customer Segmentation, Assortment Optimization, Affinity Modelling, Survival Analytics, Response Prediction, Personalization Recommendations, Channel Attribution, Marketing Mix Optimization

- Prepare case studies and white papers, and deliver seminars and workshops to demonstrate the scientific leadership of Sciative Solutions and how it delivers value to clients businesses

Qualification and Experience :

- Qualification : BE/BTech in Engineering, or Bachelor's degree in Economics, Mathematics, Computer Science, or related field

- 0 - 2 years of demonstrated hands-on experience (6+ years for Sr. Data Scientist) designing and applying ML/statistical techniques to solving complex business problems at scale

- Demonstrated experience of formulating a problem statement and implementing analytical solutions by understanding available data and functional requirements

- High proficiency in design of algorithms, design of experiments

- Experience in Machine Learning, Statistics, Operations Research techniques

- Proficiency in at least one of MlLib, R or Python's data science stack

- High Proficiency in relational databases, data management concepts and SQL scripting

- Experience in Spark preferred (but not essential)