Data Scientist - Advanced Analytics

Key Skills

Python Programming, PySpark, SQL, Apache Airflow, Databricks, Kedro, AWS, Google Cloud Platform (GCP), Azure, Scala Programming, RDBMS, PostgreSQL, Amazon RedShift, Teradata, Snowflake, NoSQL, Apache Cassandra, Neo4J, Titan, MongoDB

Job Description

Who You'll Work With

You’ll work in our Santiago office as part of our Analytics team.

McKinseyAnalytics works together with clients to build analytics-drivenorganizations. We combine the latesttechniques with deep industry, functional, and analytics expertise to helpclients capture the most value from data.

This global practice supports clients in many different industries facing challenges of developing and implementing tailored concepts for prediction and prescription. We have the freedom to try new ideas, experiment and are expected to be constantly learning and growing. There is also a strong emphasis on mentoring others in the group, enabling them to grow and learn.

What You'll Do

You will work on all aspects of the design, development and delivery of machine learning enabled solutions for our clients and consulting teams.

In this role, you will shape the future of what data-driven organizations look like, drive processes for extracting and using that data in creative ways and create new lines of thinking within an infinite number of clients and situations.

You will create valuable, transformative business strategies through the measurement, manipulation, reporting and dissemination of broad sets of data. You'll help to drive the analytical scope and method for projects, including formulating and shaping the models. Additionally, you'll develop world-class data science products for clients as well as for our data science team. You'll work on complex data sets from some of the world’s largest organisations, and you'll leverage math, statistics, and machine learning to derive key insights across various industry sectors. You will review, support and advise on the day-to-day analytics requirements of clients’ key operational processes while continually improving the impact of these processes.

Qualifications

• Undergraduate degree in math, statistics, physics or engineering; master's or PhD level in computer science, artificial intelligence, applied statistics or mathematics is a plus
• 3+ years of professional experience in programming; experience applied to business problems is a plus
• 3+ years of professional experience in applying machine learning and data mining techniques to real problems with copious amounts of data
• Ability to independently own and drive model development, balancing demands and deadlines
• Ability to prototype statistical analysis and modeling algorithms and apply these algorithms for data driven solutions to problems in new domains
• Programming experience (focus on machine learning): R and/or Python (must), SPSS, SAS, Ruby, Hadoop (valued)
• Experience in data treatment/data mining: SQL, AWK, Access, Spark, Excel (valued)
• Statistical knowledge is a plus
• Demonstrated aptitude for analytics
• Proven record of leadership in a work setting and/or through extracurricular activities
• Ability to work collaboratively and effectively in a team environment and with people at all levels in an organization
• Ability to communicate complex ideas effectively – both verbally and in writing – in English and the local office language(s)
• Willingness to travel