Data Scientist - R/Python (4-7 yrs)

Job Description :

Skills/Expertise : Python, Deep learning, Temporal/ Sequence modelling, Image processing

Overview :

A Data Scientist is responsible for analyzing complex data sets to extract meaningful insights, develop predictive models, and drive data-driven decision-making within an organization. They use statistical methods, machine learning algorithms, and programming skills to solve business problems and improve operational efficiency.

Key Responsibilities :

Data Collection & Processing :

- Gather and clean structured and unstructured data from various sources.

- Ensure data integrity and quality for analysis.

Exploratory Data Analysis (EDA) :

- Analyze large datasets to identify trends, patterns, and anomalies.

- Generate visualizations to communicate findings effectively.

Model Development & Machine Learning :

- Develop predictive models and machine learning algorithms to solve business problems.

- Optimize and fine-tune models for accuracy and efficiency.

Statistical Analysis & Hypothesis Testing :

- Perform A/B testing and statistical analysis to validate hypotheses.

- Interpret and translate data insights into actionable recommendations.

Big Data & Cloud Computing :

- Work with big data tools and cloud platforms such as Hadoop, Spark, AWS, or Google Cloud.

- Implement scalable solutions for processing large volumes of data.

Business Intelligence & Decision Support :

- Collaborate with stakeholders to understand business objectives.

- Provide insights that help improve business processes and strategy.

Data Visualization & Reporting :

- Create dashboards and reports using tools like Tableau, Power BI, or Python libraries (Matplotlib, Seaborn).

- Present findings in a clear and concise manner to both technical and non-technical audiences.

Automation & Deployment :

- Automate data processing workflows using Python, SQL, or ETL tools.

- Deploy models into production environments for real-time decision-making.

Collaboration & Cross-functional Communication :

- Work closely with data engineers, analysts, and business teams to ensure seamless data integration.

- Explain technical concepts to non-technical stakeholders.

Continuous Learning & Research :

- Stay updated with the latest trends and advancements in AI, ML, and data science.

- Experiment with new technologies and techniques to improve models and workflows.

Required Skills & Qualifications :

Technical Skills : Python, R, SQL, Machine Learning, Deep Learning, NLP, Data Engineering.

Analytical Skills : Strong problem-solving, statistical modeling, and critical thinking.

Tools & Technologies : TensorFlow, Scikit-learn, Spark, Tableau, Power BI, AWS, Google Cloud.

Soft Skills : Communication, teamwork, business acumen, and adaptability.

Education : Bachelor's/Master's in Computer Science, Statistics, Mathematics, Data Science, or related fields.