Senior 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 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