Data Science+Gen ai-Con/

  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