Data Scientist

at  Sonatus

Sonatus is looking for a highly motivated Data Scientist to join our team and help us accelerate software innovations for next-generation software-defined vehicles. We are passionate about putting our customers first and creating products that solve real-world problems.

QUALIFICATIONS AND EXPERIENCE

• MS or PhD in Computer Science, Engineering, Sciences, Applied Mathematics, or a related field.
• Minimum 5+ Years of experience
• Strong knowledge and understanding of current ML and AI technologies & platforms.
• Knowledge of current technologies and ML frameworks (tensorflow, pytorch, sklearn, keras, etc.).
• Hands-on experience with data engineering/processing frameworks (databricks, spark, dataflow, etc.).
• Data Science prototyping experience.
• Results-driven with a positive can-do attitude.
• Creative problem-solving skills.
• Experience with SQL.
• Excellent verbal and written communication skills.
• Prefer experience with distributed storage and computing tools such as Hadoop and Spark.
• Prefer working knowledge of streaming data solutions.

DESIRED SKILLS AND EXPERIENCE

• Experience in the Automotive Industry is highly desireable
  Early Career: $99,000 - $173,000
  Mid-Career: $154,000 - $249,500
  Seasoned Career: $198,500 - $300,000
  The salary range provided is a good faith estimate representative of all experience levels and what Sonatus ("Company") could reasonably expect to pay for a position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, geographic location and external market pay for comparable jobs. The Company reserves the right to modify this range in the future, as needed, as market conditions change.
  Consider being part of the Sonatus team and receive the following:

Benefit Offerings includes:

• Competitive compensation and equity program
• Health care plan (Medical, Dental & Vision)
• Flexible and Dependent Care Expense program
• Retirement plan (401k)
• Life Insurance (Basic, Voluntary & AD&D)
• Unlimited paid time off per year
• Hybrid office work-arrangement/flexibility

Perk Offerings include:

• Complimentary lunches, snacks and beverages during on-site working days
• Wellness benefit allowances (towards gym membership and fitness programs)
• Internet reimbursement
• Computer Accessory Allowance

Employee Engagement Offerings:

• Departmental team building and outings

• Employee Referral Program

• Culture/Employee Satisfaction Surveys - Feedback matters!

• Peer Award Program (monthly)

• Innovative Award Program (annual)

Sonatus is a fast-paced and innovative company and are seeking team members who are passionate about making a difference. If you are ready to take your career to the next level, we highly encourage you to apply.
To all recruitment agencies: Sonatus, Inc. ("Sonatus") does not accept unsolicited agency resumes. Please do not forward resumes to our careers alias or other Sonatus’ employees. Sonatus is not responsible for any fees associated with unsolicited activities

• Perform data analysis and offer insights to inform business decisions.
• Work collaboratively with cross-functional teams to identify and address intricate data challenges.
• Create and deploy data models and algorithms to enhance decision-making processes.
• Employ programming languages and tools for extracting, cleansing, and manipulating extensive datasets.
• Present findings and recommendations to stakeholders using visualizations and presentations.
• Stay current with industry trends and advancements in Data science.
• Take charge of projects, ensuring timely completion in a dynamic work environment.
• Engage in training and developmental activities to augment skills and knowledge.
• Adhere to data privacy and security protocols to uphold the confidentiality of sensitive information.
• Perform the full data modeling and algorithm development cycle: modeling, training, tuning, validating, deploying, and maintaining services.
• Research and develop novel statistical approaches and machine learning/deep learning models that add value to manufacturing processes and product performance improvement.
• Assess the effectiveness and accuracy of data sources and data-gathering techniques.