🏢 Company Overview:
Sigmoid is a leading data analytics and AI solutions company dedicated to helping businesses unlock the true power of data. With expertise in advanced analytics, machine learning, and data engineering, Sigmoid delivers scalable and impactful data-driven solutions to global clients across various industries. The company is known for its innovation, strong technical teams, and commitment to transforming raw data into actionable insights.
💼 Job Details:
- Employment type: Part Time
- Experience: 4 to 6 Years
- Salary: ₹45,000 – ₹65,000 monthly
- Location: Work For Home
- Work timing: 9:45 AM to 6:45 PM
- Working Days: 5 Days
- Education: Any Degree
📝 Job Description:
Sigmoid is seeking a motivated part-time Data Science professional to assist in building predictive models, analyzing complex datasets, and supporting analytics-driven decision-making. This role is ideal for individuals who are passionate about data, machine learning, and solving real-world business challenges. The selected candidate will collaborate with the analytics team and contribute to developing data-driven solutions.
🔑 Key Responsibilities:
- Analyze large datasets to extract meaningful insights
- Assist in building machine learning models and algorithms
- Perform data cleaning, preprocessing, and feature engineering
- Work with cross-functional teams to understand business requirements
- Visualize data using dashboards and analytical tools
- Support ongoing data science and analytics projects
🛠️ Required Skills & Qualifications:
- Basic understanding of machine learning and statistical concepts
- Proficiency in Python, R, or SQL
- Familiarity with libraries such as Pandas, NumPy, Scikit-learn, or TensorFlow
- Strong analytical and problem-solving skills
- Ability to communicate findings clearly
- Experience with data visualization tools (Power BI, Tableau, or Matplotlib) is a plus
- Students, freshers, or part-time job seekers are welcome to apply
🌟 Benefits:
- Opportunity to work on real-world data science projects
- Flexible part-time work schedule
- Hands-on learning and mentorship from experienced data scientists
- Exposure to cutting-edge analytics and AI technologies
- Supportive and knowledge-driven work culture
