Consultant Data Science Job in Pharmaace Analytics Pvt. Ltd.

Responsibilities: Help build an automatic forecasting tool using AI/ML, deep learning, algorithms which caters to a wide variety of datasets (and suggest an expert selected forecast based on data quality and other forecasting needs) Process automation using SQL/Python/Other available technologies/ETL Tools Estimation of economic transformations of time varying covariates. Experience with designing statistical experiments (DoE). Responsible for modelling forecasting problems, discovering insights, and identifying opportunities using statistical, machine learning, algorithmic, data mining. Applying statistical techniques such as linear regression, logistic regression, analysis of variance, cluster analysis, time series, principal components, factor analysis, ARIMA to solve business problems Come up with Hybrid statistical models to suit various analytical needs Hands on work experience with statistical machine learning and deep learning (e.g., CNN, RNN, LSTM) Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world Verifying data quality, and/or ensuring it via data cleaning Supervising the data acquisition process if more data is needed Defining validation strategies Defining the pre-processing or feature engineering to be done on a given dataset Defining data augmentation pipelines Training models and tuning their hyperparameters Interpreting and analysing both qualitative and quantitative data points; hypothesis building with Strong excel and PPT skills Process automation using SQL/Python/Other available technologies/ETL Tools Qualifications: B.Sc or M.Sc in Mathematics, Statistics, Computer science/ Data Science. Phd in Statistics Minimum 4 years of pharma / life science consulting job experience High motivation, good work ethic, maturity, and personal initiative Strong oral and written communication skills Strong excel and PowerPoint skills. Adherence to client specific data privacy and compliance policies Knowledge on various commonly used transactional data assets and others including Volumes/ Value, Rx, Specialty level, Longitudinal Patient level data assets Other competencies: Entrepreneurial orientation. Excellent interpersonal and communication skills (written and verbal). Innovative and collaborative behavior, team player. Customer centricity and paying attention to details.