Data Scientist - Trend and Predictive Analytics

Job Summary:

• We are seeking a highly skilled Data Scientist with 10+ years of industry experience to join our team. The successful candidate will have a strong background in data analysis, statistical modeling, and data visualization, as well as excellent communication skills.

Key Responsibilities:

• Data Analysis: Perform exploratory data analysis (EDA) to identify trends, patterns, and correlations; apply statistical and quantitative tools or techniques; interpret data and formulate deep-level insights.
• Setting Goals and Success Metrics: Collaborate with stakeholders to define business objectives and key results (OKRs); define success metrics that measure short and long-term progress towards OKRs.
• Visualization: Design visualizations that provide a clear narrative understanding as well as deep dive capabilities; develop high-performance reports and dashboards.
• Storytelling Through Data: Develop compelling narratives to communicate data insights for technical and non-technical audiences utilize various relevant tools and techniques to effectively present data; provide recommendations based on analytical findings and insights, with prioritization of actions and estimated impact.
• Modeling: Develop and implement predictive and forecasting models using multiple techniques such as regression, clustering, classification, and more; evaluate and refine models based on performance metrics; generate actionable insights from model output.
• Research and Experiment: Formulate multiple hypotheses that are tied together to answer business questions; develop a comprehensive research plan that identifies appropriate data collection tools, techniques, or methods to be used for specific research problem conduct research with appropriate methods to answer the research questions or test hypotheses.

Requirements:

• 10+ years of industry experience solving analytical problems using quantitative approaches, including defining metrics and goals, monitoring key metrics, understanding root causes of changes in metrics, and exploratory analysis to discover new opportunities.
• 10+ years of industry experience with data querying languages (e.g., SQL), scripting languages (e.g., Python), and/or statistical/mathematical software (e.g., R).
• Strong background in data analysis, statistical modeling, and data visualization.
• Excellent communication skills, with the ability to present complex data insights to both technical and non-technical audiences.

Minimum Years of Experience:

• 10+ Years

Must-Have Skills:

• Programming Efficiency: Ability to develop solutions to complex data problems using programming and scripting languages (SQL, Python, etc.).
• Setting Goals and Success Metrics: Ability to set clear goals, analyze data, and understand product requirements to inform business decisions and drive product success.
• Data Analysis and Storytelling: Ability to interpret and formulate deep-level insights based on quantitative and qualitative data, communicate insights in a clear and concise manner.

Nice-to-Have Skills:

• Data Visualization Expertise: Familiarity with data visualization tools such as Tableau or Power BI, to effectively communicate insights and findings to stakeholders.
• Machine Learning Proficiency: Experience with machine learning libraries and frameworks like scikit-learn or TensorFlow, to build predictive models and solve complex problems.
• Analytics/Metric Framework: Experience designing consistent and scalable analytics frameworks for open-ended questions.
• ETL and Data Modeling: Design and implement ETL process, maintain and scale large datasets and models.
• Research and Experiment: Experience identifying and designing scientific testing and research to answer strategic business questions.

Degrees/Certifications:

• Required: Bachelor's degree in Statistics, Data Science, or a related field.
• Preferred: Master's degree in Statistics, Data Science, or a related field.

Day-to-Day Responsibilities:

• Analyzing data to identify trends and patterns and developing insights to inform business decisions.
• Collaborating with stakeholders to define goals and success metrics and tracking progress towards these objectives.
• Creating visualizations and reports to communicate complex data insights to both technical and non-technical audiences.
• Developing and refining predictive models to forecast future outcomes and drive business growth.
• Conducting research and experimentation to answer key business questions and test hypotheses.

Screening Process 3 Rounds:

• Round 1: Technical Assessment (45 Minutes - 1 Hour)

Evaluate candidate's technical skills in SQL and coding.

Present a series of questions and problems to solve, assessing their ability to write efficient and effective code.

• Round 2: Case Study and Product Scenario Analysis (1 Hour)

Provide a simple data scenario related to product development.

Ask the candidate to analyze the data and present their findings, evaluating their ability to think critically and strategically.

Assess their understanding of product scenarios and how they would approach analysis and problem-solving.

• Round 3: Behavioral and Autonomy Assessment (30 Minutes)

Ask the candidate to share a story about a time when they used data to drive business decisions or tell a story with data.

Evaluate their ability to work independently and autonomously, without requiring hand-holding or close supervision.

Assess their ability to show direction and leadership in a data-driven project or initiative.