QuantumBlack, AI by McKinsey.
Austin, TX

Senior Data Scientist - QuantumBlack (Austin, TX)

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Who You'll Work With
As a Senior Data Scientist at QuantumBlack, you will work with other data scientists, data engineers, machine learning engineers, designers and project managers on interdisciplinary projects, using maths, stats and machine learning to derive structure and knowledge from raw data across various industry sectors.
Who you are
You are a highly collaborative individual who is capable of laying aside your own agenda, listening to and learning from colleagues, challenging thoughtfully and prioritizing impact. You search for ways to improve things and work collaboratively with colleagues. You believe in iterative change, experimenting with new approaches, learning and improving to move forward quickly.
Qualifications
  • MSc or PhD level in the field of computer science, machine learning, applied statistics, mathematics
  • Experience in statistical modelling and machine learning techniques
  • Programming experience in at least two of the following languages: R, Python, Scala, SQL
  • Experience in applying data science methods to business problems
  • Experience in applying advanced analytical and statistical methods in the commercial world
  • Good presentation and communication skills with the ability to explain complex analytical concepts to people from other fields
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Where we are

714 Congress Ave , Austin, TX 78701

Technology we use

  • Engineering
    • C++Languages
    • JavaLanguages
    • JavascriptLanguages
    • PythonLanguages
    • RLanguages
    • ScalaLanguages
    • SqlLanguages
    • jQueryLibraries
    • ReactLibraries
    • PandasLibraries
    • PySparkLibraries
    • DjangoFrameworks
    • HadoopFrameworks
    • JupyterFrameworks
    • Node.jsFrameworks
    • SparkFrameworks
    • TensorFlowFrameworks
    • TorchFrameworks
    • Google CloudFrameworks
    • AWS (Amazon Web Services)Frameworks
    • MS AzureFrameworks
    • HiveDatabases
    • Microsoft SQL ServerDatabases
    • MongoDBDatabases
    • SnowflakeDatabases
    • SQLiteDatabases
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What are QuantumBlack, AI by McKinsey. Perks + Benefits

Culture
Volunteer in local community
Friends outside of work
Open door policy
Team owned deliverables
Team based strategic planning
Group brainstorming sessions
Open office floor plan
Diversity
Dedicated Diversity/Inclusion Staff
Unconscious bias training
Hiring Practices that Promote Diversity
Health Insurance & Wellness Benefits
Flexible Spending Account (FSA)
Disability Insurance
Dental Benefits
Vision Benefits
Health Insurance Benefits
Life Insurance
Wellness Programs
Mental Health Benefits
Retirement & Stock Options Benefits
401(K)
Performance Bonus
Match charitable contributions
Child Care & Parental Leave Benefits
Child Care Benefits
Generous Parental Leave
Family Medical Leave
Adoption Assistance
Vacation & Time Off Benefits
Generous PTO
Paid Volunteer Time
Paid Holidays
Paid Sick Days
Perks & Discounts
Commuter Benefits
Stocked Kitchen
Happy Hours
Relocation Assistance
Professional Development Benefits
Job Training & Conferences
Tuition Reimbursement
Diversity Program
Lunch and learns
Cross functional training encouraged
Promote from within
Mentorship program
Time allotted for learning
Online course subscriptions available
Paid industry certifications

An Insider's view of QuantumBlack, AI by McKinsey.

How would you describe the company’s work-life balance?

Unique, awesome! Never had it this good. We establish team norms at the beginning of each engagement to tailor an extraordinary work/life balance, have more fulfilling and impactful workdays, and leave room for personal and family time day after day.

Ravi

Principal – Data Engineering, New York

What does your typical day look like?

The morning usually starts with check-in calls with the team. The afternoon includes problem-solving sessions with leadership to resolve roadblocks and align on next steps. Throughout the day, we have blocks of heads-down coding time to develop pipelines for data cleaning and transformation, feature engineering, etc.

Aisuluu

Senior Consultant – Data Engineering, Toronto

How does the company support your career growth?

Strong culture of encouraging people to proactively ask for and provide feedback. The company also emphasizes mentorship and apprenticeship which can provide opportunities and safe places for people to ask questions and get help if needed.

Tianfang

Data Engineering, Boston

What's the biggest problem your team is solving?

We are solving how to develop scalable machine learning tools that data scientists and engineers across our organization can use easily and quickly. We are doing this across many domains, including life sciences, GEM, banking, and more.

Sanjay

Junior Principal – Data Science, New York

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