Data Scientist

• Skill: Data Scientist
• Programming Languages: Proficiency in Python or R, plus SQL for database querying.
• Technical Skills: Machine learning, statistical modeling, data mining, and big data frameworks (e.g., Hadoop, Spark).
• Data Visualization & Tools: Experience with tools like Tableau, Power BI, or Excel.
• Soft Skills: Strong analytical thinking, problem-solving, and the ability to tell a compelling story with data. [1, 2, 3, 4, 5, 6]
• Data Preparation & Cleaning: Spend a large portion of time (often 70% to 90%) gathering, cleaning, and transforming raw structured and unstructured data. [1]
• Exploratory Data Analysis (EDA): Identify trends, patterns, and correlations using statistical methods and visualization tools. [1]
• Model & Algorithm Development: Build, test, and validate machine learning models, statistical models, and predictive algorithms. [1, 2]
• Stakeholder Communication: Translate technical findings into clear charts, dashboards, and business recommendations for non-technical teams. [1, 2]
• Cross-Functional Collaboration: Partner with data engineers, product teams, and management to integrate models into production. [1, 2]
• 1.Discretionary Annual Incentive.
• 3.Family Support: Maternal & Parental Leaves.
• 4.Insurance Options: Auto & Home Insurance, Identity Theft Protection.
• 6.Time Off: Vacation, Time Off, Sick Leave & Holidays.

None flagged.