Sr Manager - Data Science

This position supports organizational strategy and operations through design and statistical analysis of business initiatives and experiments. Works with business partners to understand what the business needs and issues are to address. Applies advanced knowledge of statistics and data mining (e.g., predictive modeling, simulation) or other mathematical techniques to recognize patterns and create insights from business data. Designs, develops, and evaluates statistical and predictive models that lead to business solutions. Serves as lead statistician for the unit, providing expertise, oversight and guidance on statistical analysis efforts. Communicates findings and recommendations to management across different departments. Supports implementation efforts

Experience & Education:

• Total experience of 10-15 years (relevant Analytics experience at least : 8 years and minimum of 3-4 Years As manager handling Team directly.) Industry Experience and knowledge especially in Manufacturing/ Operations Functions in a energy sector, automotive, Manufacturing, Process or Pharma preferred.
• Bachelors degree in data science, Computer science, Electrical Engineering, Applied Statistics, or Physics with 12+ years of relevant work experience in Data Science, Artificial Intelligence or Machine Learning algorithm development
• Master’s degree in data science, Computer science, Electrical Engineering, Applied Statistics, or Physics with 10+ years of relevant work experience in Data Science, Artificial Intelligence or Machine Learning algorithm development.
• PhD degree in Data Science, Computer science, Electrical Engineering, Applied Statistics, or Physics with 8+ years of relevant work experience in in Data Science, Artificial Intelligence or Machine Learning algorithm development

Essential Responsibilities:

• Statistical Analyis & Model Development

• Works with business partners to identify and scope new opportunities for statistical analysis applications to evaluate business performance and to support business decisions.
• Works internally and with I/S and Enterprise Data Management to define, secure and prepare datasets for statistical modeling.
• Explores data using a variety of statistical (e.g., data mining, regression, cluster analysis) techniques to answer business questions or guide future model development.
• Builds programs for running statistical tests on data and for understanding correlation of various attributes.
• Builds hypotheses, identifies research data attributes and determines best approach to address business issues.
• Working with business partners, leads development of experimental design for business initiatives.
• Applies advanced statistical techniques, including analysis of variance, t-tests, factor analysis, regression and multivariate analyses or simulation, to analyze the effects of business initiatives.
• Builds predictive models (e.g., logistic regression, generalized linear models) as appropriate to support business partner objectives.
• Builds and deploys computer vision models (e.g., image classification, object detection, segmentation) to meet business needs.
• Prepares testing scenarios and tests model performance.
• Incorporates findings and provides insights as part of model development and enhancement.
• Provides guidance and direction related to statistical analysis to less experienced Data Science & Analytics staff as needed. Provides peer review related to analytics methods and results.
• Responsible for advanced analytics, including experimental design and analysis, for the most complex business experiments.

• Model Consultation, Implementation, & Communication

• Serves as statistical expert within the unit as well as in consultation to various areas of the business, to support design and analysis of business experiments.
• Leads analytics projects or components related to large, complex business initiatives.
• Prepare recommendations and findings for business partners.
• Works with research and analytics staff and other areas of the business on model application and implementation.
• Effectively communicates and delivers statistical and predictive model results to business partners, supporting socialization and adoption of analysis results into business activities and decisions.
• Assists with knowledge transfer and training to business areas regarding new analytics applications as part of implementation process.
• Works closely with business stakeholders to identify and answer critical questions.
• Assists in development of standard analytical approaches and methodologies for the department. Provides knowledge transfer and training on new modeling and statistical analysis tools and methodologies to less experienced staff.

• Industry Research

• Researches and maintains awareness of industry best practices and business strategies.
• Proactively brings in new and innovative ideas and approaches to develop business solutions.
• Researches and leverages new statistical techniques and technologies to apply in their statistical research work.

Required Skills/Competencies:

• Minimum of 8+ years of Handson experience in advanced Machine Learning & Deep Learning techniques and algorithms such as Decision Trees, Random Forests, SVMs, Regression, Clustering, Neural Networks, CNNs, RNNs, LSTMs, Transformers, etc.
• 6+ years of experience in experience in statistical computer languages (Python, PySpark etc.) to manipulate data and draw insights from large data sets
• 5+ years of experience in Cloud platforms like AWS with specific experience of leveraging AWS services and deploying AI / ML models on these platforms
• Experience in DL frameworks such as TensorFlow, Keras or PyTorch
• Familiarity with business intelligence tools (e.g. Qlikview) and data frameworks will be an added advantage.
• Proficient with programming languages and statistical software tools (Python, SAS, R, JMP or similar), relational databases (SQL server), data analysis and visualization software (preferably PowerBI, SAS).
• Experienced with standard data science and machine learning packages such as Numpy, Pandas, Matplotlib, seaborn, bokeh, plotly
• Have solid understanding of the machine learning model stack (regression, classification, neural networks, time series) and packages (Scikit learn, Xgboost, Keras, Pytorch, Tensorflow, statsmodels)
• Have solid understanding of the machine learning model tradeoffs such as hyper-parameter tuning, regularization, cross-validation, skewness in data, dimensionality reduction, and complexity vs interpretability.
• Knowledge of and experience with utilizing advanced descriptive statistics and analysis techniques (such as forecasting, analysis of variance, t-tests, categorical data analysis, nonparametric data analysis, cluster analysis, factor analysis and multivariate statistical analysis) design business experiments and measure the impact of business actions.
• Handson experience in statistical and data science techniques
• Knowledge and experience in developing and deploying Gen AI Solution.
• Strong communication skills to work with groups, and experience with communicating business implications of complex data relationships and results of statistical models to multiple business partners.
• Strong self-direction, initiative, and ability to prioritize multiple tasks from various requestors, demonstrated ability to manage multi-faceted projects
• Excellent Technical Presentation Skills

Leadership & Soft skills:

• Lead by example on values and culture.
• Open-minded, collaborative and an effective team player.
• Ability to work in a multicultural and diverse team.
• Driven for success and aspiring to a culture of service excellence, always putting the customer, our people and our business at the center of everything he/she does.
• Ability to deal with ambiguity.
• Ability to communicate openly and effectively with many diverse stakeholders, with external vendors and auditors, and with staff.
• Ability to work proactively and under pressure considering the criticality required to ensure the right quality of service for the business.