It’s an exciting time to be working with data. Organizations everywhere are beginning to accept that data needs to be a huge part of their business. At Lixar, we have the privilege to help them get there.
- We get to solve complex and challenging data problems every day.
- We get to work on projects that directly apply knowledge in Natural Language Processing, Image Processing, Signal Processing and Frequentist Statistics.
- We employ techniques in Anomaly Detection, Classification, Clustering and Regression to build intelligent software for world class clients.
We’re looking for a Technical Team Lead with a passion for Data Science to join our practice:
- You’ll be leading brilliant people through challenging projects
- You’ll be mentoring and coaching your team to success, and participate in an extremely vibrant and engaging data community.
- You’ll work with clients and help them define and achieve their data roadmap from the Machine Learning and Artificial Intelligence perspective.
- You’ll work closely with Data Engineering and Data Visualization to bring data to life.
- Are passionate about data
- Have 6+ years of experience in a technical field with increasing responsibilities
- Have 2+ years of experience leading technical teams
- Love to program in languages like Python, Scala and R
- Have a proven ability to develop and execute sophisticated data mining & modeling solutions
- Have strong attention to detail and excellent quantitative and qualitative analytical abilities
- Know your way through at least a few major relational DBs
- Communicate exceptionally well with management, peers, and clients
- Have a sense of humour
You may be the person we’re looking for!
Send your résumé and salary expectations to Lixar today!
email@example.com | firstname.lastname@example.org
Thank you for applying! We look forward to meeting with the selected interview candidates.
Lixar IT welcomes and encourages applications from people with disabilities. Accommodations are available on request for candidates taking part in all aspects of the selection process.