Job description

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 clients' 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 which 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 experience with ETL ,data processing , data programming and data analytics
 Experience with Big Data processing (Spark/Bigquery / Hive/ Hadoop/ HDFS)
 Experience of R, SQL and Python;
 Experience of 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 modelling
 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 behavioural attributes
 Proactive and highly organised, 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 is a plus.
 Strong Leadership, professional attitude – and leading by example
 Passionate about IT and good understanding of emerging IT technologies is important
 Ability to multi-task and stay organised 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

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