Data Scientist

We are seeking a highly skilled Data Scientist to join our team and drive our data-driven initiatives. As an experienced Data Scientist, you will play a pivotal role in leveraging data to uncover valuable insights and inform strategic decision-making. You will work closely with cross-functional teams to develop and implement advanced data analytics solutions that support our business goals.

Key Responsibilities:

A) Business Problem Solving through Data Science:

1. Engage with business stakeholders to understand their challenges, business objectives, and opportunities for data-driven decision-making.
2. Translate business problems into well-defined analytical tasks and design data science solutions that align with business goals.
3. Proactively identify areas within the business where advanced analytics can provide significant impact, such as customer behavior analysis, pricing optimization, or process automation.

B) Data Exploration & Analysis:

1. Perform exploratory data analysis (EDA) to identify trends, patterns, and insights from structured and unstructured data sources.
2. Clean, preprocess, and transform data to prepare it for modeling and analysis.
3. Collaborate with data engineers and IT teams to ensure data pipelines are robust, scalable, and accurate.

C) Predictive Modeling & Algorithm Development:

1. Build, train, and deploy predictive models (e.g., regression, classification, clustering, time series analysis) to solve key business problems.
2. Apply machine learning techniques to develop models for tasks such as customer segmentation, churn prediction, demand forecasting, and recommendation systems.
3. Use tools such as Python, R, SQL, and cloud-based platforms to implement and scale predictive models.

D) Data-Driven Solutions & Decision Support:

1. Develop data science-driven solutions and tools that improve business decision-making across functions such as marketing, sales, operations, and finance.
2. Generate actionable insights from data models and communicate results effectively to non-technical stakeholders, translating complex analyses into simple, business-focused recommendations.
3. Use optimization techniques to enhance business processes, improve efficiency, and reduce costs.

E) Performance Monitoring & Model Refinement:

1. Continuously monitor the performance of deployed models and refine them as necessary to ensure long-term accuracy and relevance.
2. Implement A/B testing and other experimental methods to validate model outcomes and assess business impact.
3. Collaborate with teams to integrate predictive models into business workflows and decision-making processes.

F) Cross-Functional Collaboration:

1. Work closely with business leaders, product managers, marketing teams, and other stakeholders to ensure data science initiatives align with strategic objectives.
2. Partner with data engineering teams to ensure data availability and quality, and to build scalable solutions.
3. Mentor and train team members on data science methodologies and best practices.

What you will need:

• Advanced degree in Data Science, Statistics, Computer Science, or a related field.
• Minimum 5 years of experience in data science, with a strong focus on machine learning and predictive modeling.
• Proficiency in Python, R, or similar programming languages.
• Expertise in data visualization tools (e.g., Tableau, Power BI).
• Strong understanding of statistical concepts and techniques.
• Experience working with cloud platforms (AWS, GCP, Azure) and big data technologies (Hadoop, Spark).
• Excellent problem-solving and analytical skills.
• Strong communication and interpersonal skills, with the ability to collaborate effectively with both technical and non-technical teams.

Additional Preferred Qualifications

• Experience in automotive, manufacturing/logistics
• Knowledge of specific machine learning techniques (e.g., deep learning, natural language processing).
• Experience with data governance and compliance frameworks.