Sr Data Scientist

Roles and Responsibilities

• Own and execute analytics-related projects.


• Independently interact with internal/external clients to understand requirements and provide updates


• for Proposal or Execution, as the case may be.


• Understand client's business questions and develop solution architecture.


• Build predictive models and machine-learning algorithms


• Solve business problems by applying advanced Machine Learning algorithms and complex statistical


• models on large volumes of data.


• Demonstrate strong thought leadership and consult with product and business stakeholders to build,


• scale and deploy holistic data science products after successful prototyping.


• Define an analytics plan and delivery schedule.


• Develop comprehensive models/codes for specific use cases (like segmentation, forecasting, prediction


• key driver analysis, price elasticity, prediction ) that can be used in a productized form with 'no


• requirement of manual intervention' once they are developed..


• Ensure end-to-end implementation of the developed modules on the products.


• Develop and distribute product strategies for analytics-related interventions


• Performs research and applies new techniques and concepts to solve problems


• Provide thought leadership, perform Advanced Statistical Analytics, and create insights into data to


• provide to the business actionable insights, identify trends, and measure performance that address


• business problems.


• Collaborate with business and process owners to understand business issues, and with engineers to


• implement and deploy scalable solutions, where applicable.
  

Desired Candidate Profile

• A Master s or higher degree in Computer Science, Statistics, Mathematics, or related disciplines


• 10+ years of experience with ETL,data processing, data programming, and data analytics


• Experience with Big Data processing (Spark/Bigquery / Hive/ Hadoop/ HDFS)


• Experience in R, SQL, and Python;


• Experience working with tools over AWS / Azure on big data analysis.


• Experience in data mining and statistical analysis


• Proficiency in machine learning algorithms such as decision trees, support vector machines,


• Gradient Boosting Machines (GBM), Random Forest, Regularized regression models, time series


• forecasting, anomaly detection, etc.


• Strong understanding of probability and statistical models (generative and descriptive models)


• Experience in pattern recognition and predictive modeling


• Understanding of machine learning and operations research


• Ability to run experiments scientifically and analyze results.


• Understanding of machine-learning and operations research.


• Ability to effectively communicate technical concepts and results to business audiences in a


• comprehensive manner.


• Experience with Performance Engineering including testing, tuning, and monitoring tools will be add on
  

Key behavioral attributes

• Proactive and highly organized, with strong time management and planning skills


• Able to meet tight deadlines and remain calm under pressure


• Experience working with key stakeholders at senior levels.


• Demonstrable relationships with IT vendors are a plus.


• Strong Leadership, professional attitude – and leading by example


• Passionate about IT and good understanding of emerging IT technologies are important


• Ability to multi-task and stay organized in a dynamic work environment


• Analytical and inquisitive, with excellent attention to detail


• Credible, confident, and articulate, with excellent communication and presentation skills and the


• gravitas to deliver ideas clearly and concisely to internal and external stakeholders


• Personable and approachable, with an enthusiastic and motivational nature and an overall


• passion for excellence