Manager - Analytics Architect and Data Scientist

Could you be Avanade’s next Analytics Architect / Data Scientist superstar?

As an Industry Analytics Architect and Data Scientist, you will help clients understand and extract insight and value from their data using Machine Learning and AI techniques. Working as part of a team, you will be involved in all phases of analytics projects, including question formulation, design, research and development, implementation, and testing. This role will explore and understand data and build advanced solutions that could be predictive, prescriptive, or optimize. You will translate real world problems into quantitative language, find or build algorithms to solve those problems, and implement them in code.

**Responsibilities**:
Data & AI Technical Responsibilities

You will support the design, implementation and optimization of trained models based on Machine Learning and Artificial Intelligence. You will work closely with program managers and bid teams to maximize the business development capacity and leverage Avanade capabilities. You will facilitate and execute requirements gathered during analysis and design phases and assist in driving business development initiatives with major stakeholders.
- Lead complex project teams and/or programs of our AI/ML offerings and will be accountable for the overall planning, management, and delivery of assigned projects/programs.
- Be responsible for the successful delivery of projects as measured by contracted scope, schedule, financials as well as overall deliverable quality and customer satisfaction
- Support sales and delivery and will be accountable for planning, mobilization, execution, and successful closure of projects.
- Communicate status with regular frequency, manage risks as well as monitor and manage financial performance according to in place agreements made between Avanade and the customer during project life cycles.
- Manage delivery of a portfolio of AI/ML projects - monitoring, escalating, managing, and resolving issues.
- Manage the data dependencies for the ML Models, Test and Validation cycles, Model Accuracy requirement.
- Develop, implement, and maintain a detailed project work plan, including appropriate controls, governance structures and monitoring to ensure on-time, on-budget, and quality outcomes.

**Skills and Capabilities**:

- Previous experience as being client facing and working in project-based consulting.
- Your knowledge includes assessing and handling the opportunities and risks associated with large scale, complex projects for your enterprise clients.
- You should already have a sound knowledge in the field of mathematics and statistics and initial experience in some of the areas of advanced analytics, natural language processing, data mining, data preparation and feature engineering.
- You should be familiar with Azure Cognitive Services and ideally you have already gained practical experience in the implementation of AI solutions as well as getting to know some of the common supervised and unsupervised machine learning models.

**Desired Experience**:

- Experience using statistics and data science.
- Experience developing machine learning using clustering, regression, optimization, recommendation, and neural networks, among other techniques.
- Experience with data science tools like Python, R, Scala, Julia, SAS, SPSS, MATLAB, Hadoop, or Spark.
- Experience working with cloud services like AWS, Google, and Azure.
- Proven leadership experience in an academic, extracurricular or professional setting.
- Demonstrable professional experience with data mining, analysis, modeling, of large scale, complex data sets.
- Proficient in statistical modeling tools and Cognitive analytics like text analytics, image recognition, video analytics etc.
- Machine learning algorithms, such as Gradient Boosting, XGBoost, Random Forests.
- Time Series Forecasting models such as Prophet, ARIMA.
- Natural Language Processing techniques such as sentiment analysis, Regex rules, intent detection, fuzzy text matching.

**Preferred Education**:
You likely possess an advanced degree (Master’s or PhD) in machine learning, analytics, computer science, physics, applied mathematics, statistics or an equivalent combination of education and experience.