Data scientist

SCOPE OF RESPONSIBILITY:

The Data Scientist will be responsible for designing and implementing data-driven solutions to address complex business challenges. They will work closely with cross-functional teams, including data engineering, product managers, and business stakeholders, to deliver actionable insights and predictive models. The role requires a balance of technical expertise and the ability to communicate complex findings to non-technical audiences.

PURPOSE OF THE POSITION:

The purpose of this position is to leverage data science methodologies to drive business innovation. The Data Scientist will focus on developing advanced analytics models, optimizing data pipelines, and contributing to the development of AI-driven solutions that enhance decision-making and create value for the organization.

RESPONSIBILITIES:

·       Responsible for end-to-end project lifecycle, from business requirements analysis to launch.

·       Analyze large datasets to uncover trends, patterns, and insights. Develop, validate, and deploy predictive models and algorithms using machine learning, deep learning, and statistical techniques.

·       Collaborate with data engineering teams to design, develop, and optimize data pipelines, ensuring data quality and availability for analytical purposes.

·       Apply AI techniques to solve business problems. Develop and integrate AI models into existing processes, focusing on scalability and performance.

·       Create interactive dashboards and visualizations using tools like Tableau and Palantir tools (Slate, Contour, Workshop) to communicate insights to stakeholders.

·       Work closely with business stakeholders to understand their needs and translate them into analytical solutions. Communicate findings and recommendations effectively to both technical and non-technical audiences.

·       Participate in knowledge-sharing sessions and contribute to the upskilling of team members.

EDUCATION:

·       Master’s degree in data science, Computer Science, Statistics, Mathematics, or a related field.

·       Minimum 3 to 5 years’ direct hands-on experience in data analytics roles.

·       Solid project management skills, and ability to drive multiple projects simultaneously. Practice or knowledge of Agile development methodologies is a plus.

EXPERIENCE:

·       3 to 5 years of professional experience in data science, or a related role.

·       Proven experience in developing and deploying machine learning models and AI-driven solutions.

·       Hands-on experience with data visualization tools and programming languages.

·       Experience in Palantir would be added advantage.

TECHNICAL SKILLS:                                                                                                    

·       Data Visualization: Proficiency in Tableau, and Palantir tools (Slate, Contour, Workshop).

·       Programming Languages: Strong knowledge of Python, PySpark, and SQL.

·       AI: Experience with ML/DL frameworks (TensorFlow, PyTorch, and Scikit-learn,Etc). Knowledge of NLP and GenAI techniques.

·       Statistics & Mathematics: Solid understanding of statistical methods, probability, and mathematical modeling.

·       Data Manipulation: Experience with data wrangling, cleaning, and preprocessing techniques. Proficiency in handling large datasets using SQL and PySpark.

·       Knowledge in MLOps tools is an added advantage.

·       Experience in Cloud platform: AWS, Azure and GCP

REQUIRED SKILLS:

·       Problem-Solving: Strong analytical skills with the ability to break down complex problems and develop data-driven solutions.

·       Communication: Excellent verbal and written communication skills, with the ability to convey technical information to a non-technical audience.

·       Previous experience in a business function (sales, customer excellence, marketing, product management, etc.) is a very strong asset.

·       Able to thrive in a complex matrixed and international environment.

·       Collaboration: Ability to work effectively in cross-functional teams and manage multiple stakeholders.

·       Attention to Detail: Meticulous attention to detail, ensuring accuracy and quality in all deliverables.

·       Time Management: Strong organizational skills with the ability to prioritize tasks and meet deadlines in a fast-paced environment.