Gen AI and Machine Learning Data Scientist

Education: Master’s in data science, Statistics, Computer Science, or a related field.
Experience: 3+ years of experience in data science, analytics, or a related field.

Technical Skills:
·        Proficiency in programming languages such as Python or R.
·        Good understanding of statistical principles for ML applications
·        Experience with data manipulation and analysis using libraries such as pandas, NumPy, and SciPy.
·        Exceptional knowledge of Deep Learning techniques, model architectures, and parameter fine-tuning
·        Very good knowledge of GenAI with good understanding of foundation models and transformer architecture
·        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 with cloud platforms (e.g., AWS, Google Cloud, Azure).
·        Familiarity with version control systems (e.g., Git).
·        Experience in genomics

Job Responsibilities:
·        Data Analysis: Analyze large, complex datasets to identify trends, patterns, and insights that inform strategic 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