AI ML (Data Science) Practitioner

Qualifications:

? Bachelors/Masters degree in Statistics, Mathematics, Econometrics, or Operations Research.

? Open to candidates from top university

? Business Analytics students aspiring to be hands-on data scientists may also apply.

? Strong knowledge in statistical concepts, Machine Learning, Hypothesis testing, DOE, and both Frequentist & Bayesian modeling techniques.

? Proficiency in Regression Modeling, Time Series Forecasting, MS Office, and programming languages R or Python.

? Experience with R libraries (dplyr, ggplot2, caret, etc.) and Python libraries (pandas, scikit-learn, numpy, etc.) preferred.

? Knowledge of SQL and AWS is a plus.

? Candidates should not be pursuing any other internships.

? Relevant work experience (2 - 3 years) is beneficial but not mandatory.

Responsibilities:

? Applying statistical and ML techniques to real business problems in Marketing Analytics, Finance, and Manufacturing.

? Engaging in R&D on Statistical Techniques, Machine Learning algorithms, and Time Series Forecasting.

? Helping develop innovative data science products.

? Applying Dynamic Time Warping to boost lead generation.

? Applying Markov Chain to effectively measure attribution.

? Proving effectiveness of Marketing campaigns via counterfactuals and causal inference.

? Applying Marketing Mix Model (MMM) to yield better Marketing ROI for companies.

? Applying NLP techniques to discern customer feedback thereby helping Brands improve their Brand Equity

? Applying Time Series techniques to better manage inventory and supply

chain.

? Applying Game theory + MMM to preempt a competitors marketing move.

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? You will learn to apply statistical and ML techniques to real business problems in domains such as Marketing Analytics, Finance and Manufacturing.

? You will be doing interesting R&D on Statistical Techniques, Machine Learning algorithms and Time series forecasting algorithms.

? You will help develop innovative data science products.