SysTechCorp - Data Scientist (4-7 yrs)

Key Responsibilities :

- Data Analysis & Exploration : Analyze large, complex datasets to identify trends, patterns, and anomalies that can lead to actionable business insights.

- Machine Learning Model Development : Build, test, and deploy machine learning models for predictive and prescriptive analytics, including regression, classification, clustering, and recommendation systems.

- Data Preprocessing & Cleaning : Prepare and clean datasets for analysis, including handling missing values, outliers, and ensuring data integrity.

- Feature Engineering : Create meaningful features from raw data to improve the performance of machine learning models.

- Model Evaluation & Tuning : Evaluate and fine-tune machine learning models using various metrics, ensuring they meet performance and business objectives.

- Collaboration : Work closely with business stakeholders to understand their data requirements and provide solutions that align with business goals.

- Data Visualization & Reporting : Present data-driven insights and model results using visualization tools (e.g. , Tableau, Power BI) and communicate findings to both technical and non-technical stakeholders.

- Continuous Learning : Stay up to date with the latest advancements in data science, machine learning, and AI technologies, and apply them to improve processes and solutions.

Required Skills & Qualifications :

- 4+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or similar role.

- Strong proficiency in Python (or R) and machine learning libraries (e.g. , Scikit-learn, TensorFlow, Keras, PyTorch).

- Solid understanding of statistics and data analysis techniques.

- Experience with SQL and working with relational databases (e.g. , MySQL, PostgreSQL).

- Expertise in data preprocessing, feature engineering, and data wrangling techniques.

- Familiarity with big data technologies (e.g. , Hadoop, Spark, Hive) is a plus.

- Experience with model deployment and using cloud platforms (e.g. , AWS, Azure, Google Cloud) for scaling machine learning models is a plus.

- Strong experience with data visualization tools such as Tableau, Power BI, or Python libraries like Matplotlib, Seaborn, or Plotly.

- Excellent communication skills with the ability to present complex findings in a clear, concise manner to both technical and non-technical audiences