Lead Data Science Deep Learning

Hi,

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I hope you are doing great today.

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Our client is looking to procure qualified candidates for the Sr Data Science Lead Deep Learning Enclosed below is the Job Description for your reference. Kindly forward the resumes of qualified candidates in Word format, Contact details, Submission process format and Skill Matrix for further processing.

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Title: Data Science Lead Deep Learning

Location: Santa Clara, CA, USA (Dayone Onsite role.. No Remote No Hybrid. Local Consultants only)

Duration: 6-12 Months Contract

Hourly rate: 65/hr C2C maxx

Number of Position: 1

Its for Implementation partner

Note: NO "Stem OPT", CPT and Transfer cases consultants are not workable for this role.

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Job Requirements

1. A minimum of 7 years of experience in Data Science, with a proven track record of delivering impactful data-driven solutions.

2. A minimum of 2 years of experience as Lead

3. In-depth expertise in statistical analysis, machine learning algorithms, and predictive modeling techniques.

4. Strong programming skills in languages such as Python, etc., with experience in data manipulation, cleaning, and analysis.

5. Experience in leading and managing a team of data scientists, including setting goals, providing guidance and feedback, and ensuring project success.

6. Proven ability to effectively communicate complex technical concepts to both technical and non-technical stakeholders.

7. Strong problem-solving skills and the ability to think strategically to identify opportunities for leveraging data and analytics to drive business outcomes.

8. Familiarity with cloud platforms, such as DataBricks or Cloudera, and experience in deploying and managing data science models in a cloud environment.

9. Strong project management skills, with the ability to prioritize and manage multiple projects simultaneously.

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Qualifications

1. Master's or Ph.D. degree in a quantitative field such as Data Science, Computer Science, Statistics, Mathematics, or a related field.

2. Proven experience in leading and managing a team of data scientists, including hiring, training, and mentoring.

3. Strong domain knowledge in a specific industry or sector, such as semiconductor or material science.

4. Publications or research experience in the field of data science, machine learning, or related areas.

5. Experience in working with unstructured data, such as text or image data, and applying natural language processing or computer vision techniques.

6. Knowledge of advanced analytics techniques, such as deep learning or reinforcement learning.

7. Experience in working with data engineering teams to build and optimize data pipelines for data processing and analysis.

8. Familiarity with data privacy and security regulations, and ensuring compliance in data science projects.

9. Strong business acumen and the ability to understand and align data science initiatives with business goals and objectives.

10. Active participation in data science communities, conferences, or meetups, and a passion for staying up-to-date with the latest advancements in the field

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