What you'll do:

• Acquire, clean, and preprocess large datasets from various sources to ensure data quality and usability.
• Conduct exploratory data analysis to understand patterns, trends, and relationships within the data.
• Design and develop machine learning models and algorithms to solve specific business problems such as predictive maintenance, customer segmentation, churn prediction, etc.
• Evaluate model performance using appropriate metrics and validation techniques. Fine tune models to improve accuracy, scalability, and efficiency.
• Deploy models into production environments, ensuring seamless integration with existing systems and processes.
• Collaborate with cross-functional teams including software engineers, product managers, and domain experts to define project requirements, prioritize tasks, and deliver solutions.
• Communicate findings and insights effectively to stakeholders through data visualization, reports, and presentations.
• Stay abreast of the latest developments in data science, machine learning, and related fields. Apply new methodologies and technologies to enhance existing solutions and explore new opportunities.

What makes you a great fit:

• Programming Skills – knowledge of statistical programming languages like R, Python, and database query languages like SQL, Hive is desirable.
• Should be an expert in Python programming.
• Familiarity with Java, Scala is an added advantage.
• Statistics – Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators, etc.
• Good exposure to Machine Learning and NLP would be preferred.
• Strong Math Skills (Multivariable Calculus and Linear Algebra) - Understanding the fundamentals of Multivariable Calculus and Linear Algebra is important as they form the basis of a lot of predictive performance or algorithm optimization techniques.
• Experience with Data Visualization Tools like matplotlib, ggplot, d3.js., Tableau that help to visually encode data
• Hands-on experience with data science tools
• Analytical mind and great business sense
• Proven Experience as Data Analyst or Data Scientist
• Programming experience in Python, Django framework, Numpy/ Pandas and understanding of ML.
• Excellent experience in Python scripting, scraping, analytics pipelines etc
• Good understanding of SQL, NoSQL, MongoDB, ORMs
• Understand Linux, basic dev ops and deployment skills
• Experience writing REST APIs, containers etc.
• Excellent Communication Skills – it is incredibly important to describe findings to a technical and non-technical audience.
• Exposure to AWS, Snowflake, Big Data would be an added advantage