In the Story of Snappfood, we believe in creating value that goes beyond the ordinary. We are wiling to establish innovative tendencies and are eager to have you on our team to help us get through our business challenges with creativity, intelligence, and agility.
We are waiting for you to continue this story.
Responsibilities:
• Analyze large and complex datasets to extract meaningful insights and trends.
• Develop and implement machine learning models and algorithms for predictive and prescriptive analytics.
• Design and execute experiments to test hypotheses and improve models.
• Collaborate with cross-functional teams to identify business problems and provide data-driven solutions.
• Develop data-driven strategies and recommendations to optimize business processes and decision-making.
• Communicate findings and insights to non-technical stakeholders through visualizations, reports, and presentations.
• Stay updated with the latest advancements in data science techniques, tools, and technologies.
• Ensure data integrity, quality, and security throughout the data lifecycle.
• Collaborate with data engineers and IT teams to ensure efficient data collection, storage, and processing.
• Mentor and provide guidance to junior data scientists or analysts.
Requirements:
• At least 3 years of experience in data science or a related field.
• Proficiency in programming languages such as Python or R, along with libraries like TensorFlow, PyTorch, or scikit-learn.
• Experience in working with relational databases, SQL, and data querying.
• Strong understanding of statistical analysis, machine learning algorithms, and their applications.
• Demonstrated experience in handling and analyzing large datasets using statistical and machine learning techniques.
• Ability to preprocess and clean raw data for analysis, handling missing values, outliers, and feature engineering.
• Proficiency in data manipulation, transformation, and analysis using Python, R, or similar tools.
• Experience with implementing and evaluating various machine learning techniques, such as regression, classification, clustering, and deep learning.
• Knowledge of data mining techniques and familiarity with tools like Spark or Hadoop.
• Understanding of data visualization principles and experience in creating clear and informative visualizations.
• Knowledge of data visualization tools like Tableau, Power BI, or matplotlib.
• Familiarity with cloud platforms like AWS, Azure, or Google Cloud for data storage and processing.
• A master’s or Ph.D. degree in a relevant field such as Data Science, Computer Science, Statistics, Mathematics, or a related discipline.
Benefits:
• Vouchers for vacation, Gym, Therapy Sessions, Intervnet Costs
• Complementary Insurance
• Educational platform of advanced courses
• Snappfood’s Discount codes
• Loans