Data Science+Gen ai-Con/Sn.Con/Man/AD – ON-SITE

Job Overview

  Work with business stakeholders and cross-functional SMEs to deeply understand business context and key business questions

  Create Proof of concepts (POCs) / Minimum Viable Products (MVPs), then guide them through to production deployment and operationalization of projects  Influence machine learning strategy for Digital programs and projects  Make solution recommendations that appropriately balance speed to market and analytical soundness  Explore design options to assess efficiency and impact, develop approaches to improve robustness and rigor  Develop analytical / modelling solutions using a variety of commercial and open-source tools (e.g., Python, R, TensorFlow)  Formulate model-based solutions by combining machine learning algorithms with other techniques such as simulations  Design, adapt, and visualize solutions based on evolving requirements and communicate them through presentations, scenarios, and stories  Create algorithms to extract information from large, multiparametric data sets  Deploy algorithms to production to identify actionable insights from large databases  Compare results from various methodologies and recommend optimal techniques  Design, adapt, and visualize solutions based on evolving requirements and communicate them through presentations, scenarios, and stories  Develop and embed automated processes for predictive model validation, deployment, and implementation  Work on multiple pillars of AI including cognitive engineering, conversational bots, and data science  Ensure that solutions exhibit high levels of performance, security, scalability, maintainability, repeatability, appropriate reusability, and reliability upon deployment  Lead discussions at peer review and use interpersonal skills to positively influence decision making  Provide thought leadership and subject matter expertise in machine learning techniques, tools, and concepts; make impactful contributions to internal discussions on emerging practices  Facilitate cross-geography sharing of new ideas, learnings, and best-practices

Requirements

Bachelor of Science or Bachelor of Engineering at a minimum.

  4+ years of work experience as a Data Scientist  A combination of business focus, strong analytical and problem-solving skills, and programming knowledge to be able to quickly cycle hypothesis through the discovery phase of a project  Advanced skills with statistical/programming software (e.g., R, Python) and data querying languages (e.g., SQL, Hadoop/Hive, Scala)  Good hands-on skills in both feature engineering and hyperparameter optimization  Experience producing high-quality code, tests, documentation  Experience with Microsoft Azure or AWS data management tools such as Azure Data factory, data lake, Azure ML, Synapse, Databricks  Understanding of descriptive and exploratory statistics, predictive modelling, evaluation metrics, decision trees, machine learning algorithms, optimization & forecasting techniques, and / or deep learning methodologies  Proficiency in statistical concepts and ML algorithms  Good knowledge of Agile principles and process  Ability to lead, manage, build, and deliver customer business results through data scientists or professional services team  Ability to share ideas in a compelling manner, to clearly summarize and communicate data analysis assumptions and results  Self-motivated and a proactive problem solver who can work independently and in teams