Gen AI Data Scientist

6 days ago Be among the first 25 applicants Education: Ph.D. degree in Data Science, Statistics, Computer Science, or a related field. Experience: 5+ years of experience in data science, analytics, or a related field.

Qualifications

Must Have Technical/Functional Skills:

Education: Ph.D. degree in Data Science, Statistics, Computer Science, or a related field. Experience: 5+ years of experience in data science, analytics, or a related field.

Technical Skills

Proficiency in programming languages such as Python or R. Proficiency in statistical/empirical model building Extensive experience with time series data, analysis, and modeling Strong knowledge of statistical principles and machine learning techniques (e.g., regression, classification, clustering, neural networks). Experience with data manipulation and analysis using libraries such as pandas, NumPy, and SciPy. Familiarity with data visualization tools (e.g., Matplotlib, Seaborn). Experience with SQL and relational databases. Knowledge of big data technologies (e.g., Hadoop, Spark) is a plus. Soft Skills: Excellent problem-solving abilities, strong communication skills, and the ability to work effectively in a team environment.

Additional Skills (Preferred)

Experience in deploying AI based solutions in manufacturing environment. Experience with cloud platforms (e.g., AWS, Google Cloud, Azure). Familiarity with version control systems (e.g., Git).

Roles & Responsibilities

Data Analysis: Analyze large, complex datasets to identify trends, patterns, and insights that inform business decisions. Model Development: Develop, implement, and validate predictive models and machine learning algorithms to solve various business problems. Data Cleaning: Preprocess and clean data to ensure its quality and integrity before analysis. Visualization: Create data visualizations and dashboards to communicate findings to stakeholders in a clear and concise manner. Collaboration: Work closely with cross-functional teams, including engineering, product management, and marketing, to understand their data needs and provide relevant insights. Reporting: Generate comprehensive reports and presentations that summarize key findings and recommendations. Continuous Improvement: Stay up-to-date with the latest developments in data science, machine learning, and related fields, and apply this knowledge to improve existing processes and methodologies.

Salary Range: $89,100-$180,000 a year

Seniority level

Seniority level Mid-Senior level Employment type

Employment type Full-time Job function

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