IT Advisor - Technology Consulting - Data and Analytics-Data Science - Manager - Multiple Positions

Key Skills

Microsoft-Excel, Java Programming, Python Programming, SQL, Azure, AWS, RDBMS, Apache Hadoop, Scala Programming, A/B Testing, NoSQL, NumPy, Pandas, Apache Pig, Google Cloud Platform (GCP), R Programming, C# Programming, ETL frameworks, PyMongo

Job Description

Work with a wide variety of clients to deliver the latest data science technologies and operations research techniques and practices to design, build and maintain scalable and robust solutions that unify, enrich and analyse data from multiple sources. Help clients navigate the complex world of modern data science and analytics. Provide clients with a unique business perspective on how data science and analytics can transform and improve their entire organization – starting with key business issues they face. Clarify problems by driving to understand the true issue. Solve problems by incorporating data into decision making. Apply data mining and statistical analysis techniques like hypothesis testing, segmentation and modelling to analyze large amounts of data. Help clients make data-driven decisions by working with structured and unstructured data sets, building out predictive models and advising our clients on data mining leading practices. Build and apply data analysis algorithms including data mining, statistics, machine learning, natural language processing, sentiment analysis, and text mining. Design, architect and develop solutions leveraging data technologies including ORACLE, AWS and teradata to ingest, process and analyze large, disparate data sets to exceed business requirements. Unify, enrich and analyze customer data to derive new insights and opportunities. Leverage in-house data platforms and recommend and build new data platforms/solutions as required. Communicate findings, recommendations and opportunities to improve data systems and solutions. Demonstrate a deep understanding of and have the ability to teach data science, concepts, tools, features, functions and benefits of different approaches to apply them. Apply a data driven approach (KPIs) in tying technology solutions to specific business outcomes. Look for opportunities for improving methods and outcomes. Collaborate, influence and build consensus through constructive relationships and effective listening.

Manage and motivate teams with diverse skills and backgrounds. Consistently deliver quality client services by monitoring progress. Demonstrate in-depth technical capabilities and professional knowledge. Maintain long-term client relationships and networks. Cultivate business development opportunities.

Full time employment, Monday – Friday, 40 hours per week, 8:30 am – 5:30 pm.

MINIMUM REQUIREMENTS:

Bachelor's degree in Mathematics, Information Systems, Statistics, Operations Research or Computer Science, and 5 years of progressive, post-baccalaureate related work experience; or a Master's degree in Mathematics, Information Systems, Statistics, Operations Research or Computer Science and 4 years of related work experience

• Must have 4 years of advisory professional services or consulting experience
• Must have 4 years hands-on experience with data science and data engineering
• Must have 4 years of experience connecting data sources and structures including: APIs, NoSQL, RDBMS, Hadoop, S3, Blob Storage
• Must have 3 years of experience with statistical modeling, ETL and data ingestion/cleansing
• Must have 3 years of experience using advanced analytics to solve business problems
• Must have 4 years of experience setting up data and experimental platforms
• Must have 4 years of experience with R, Python, Java/C# and Scala, SQL Hive and Pig
• Must have 3 years of experience with Machine learning using k-NN, naive bayes, decision trees, SVM
• Must have 4 years of Experience using data mining and statistical tools
• Must have 4 years of Hands-on experience with various big data technologies in one or more of the following ecosystems: Hadoop, AWS or Microsoft
• Must have 2 years of experience in cloud big data engineering with one of the following: AWS, Azure or GCP
• Must have 2 years of experience with solid pattern recognition and predictive modelling skills
• Must have 2 years of experience with recommendation engines, scoring systems, A/B testing
• Must have 4 years of experience working with multiple tools/libraries including Panda, NumPy, PyMongo and R
• Must have 2 years of experience managing global teams
• Travel is required approximately 80% of the time
• Any suitable combination of education, training, or experience is acceptable.