Data Scientist - KPO

Responsibilities

- Work on advanced data analysis to provide insights to different types of users

- Conduct predictive analysis to create various what-if scenarios to drive organizational planning and marketing strategy

- Be the go-to person for the data science projects within the organization.

- Design, Develop and code scripts

- To cleanse, integrate and evaluate large datasets from multiple disparate sources including unstructured data

- To embed Machine learning algorithms and automate processes.

- Construct predictive ML models, algorithms, and probability engines; verifies model and algorithm effectiveness based on actual results.

- Produces actionable & compelling recommendations by interpreting, exploring, identifying and communicating insights discovered within complex data sets.

- Mentors junior members of the team about best practices of algorithm design, scripting language, and solution documentation.

Key Desired Skills

- Graduates Engineering, Operation Research, Mathematics, Statistics, Marketing preferred

- Strong working experience on developing predictive machine learning models i.e. Classification and Regularized Regression and/segmentation/Clustering is a must.

- Exposure and thorough theoretical and practical understanding of at least one Machine Learning techniques such as Logistic Regression, Random Forest, Gradient Boosting Machines (GBM/XGB), Neural Networks, SVM's.

- Strong coding skills in R/Python must and other open source software's such Pig, hive, Mahout, etc. preferred.

- Exposure onDiscrete Choice Modeling, Design of experiment, associative mining, latent class modeling, Time Series forecasting is added advantage.

- Ability to learn and continuously adapt to everchanging space of ML algorithms and technologies and apply in practical business problems.

- Ability to independently drive innovative programs & work in an agile model.

- Ability to consult as a subject matter expert on complex client projects.

Complimentary Skills

Candidate should fulfill the - Key Skills- criteria first.

- Experience in consumer and brand analytics, campaign analysis, concept testing of products, competitor analysis, promotion analysis, etc.

- Exposure with consumer survey questionnaire designs and/or data structure (if using syndicated data) is desirable

- Exposure to product assortment planning, consumer choice models, KANO, Shapley and Turf(Total Unduplicated Reach & frequency) is added advantage