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