Data Scientist

Valiance Solutions; Bengaluru; On-site; INR 1,000,000 - 1,400,000; Full time

Job summary

A data analytics firm in Bengaluru is looking for a skilled Data Scientist to enhance demand forecasting accuracy for the retail industry. This role entails analyzing data, optimizing pre-trained models, and clearly communicating insights to non-technical stakeholders. Ideal candidates should possess 3-6 years of experience in data science, proficiency in Python and SQL, and a strong focus on problem-solving and communication. This position offers an opportunity to impact business decisions significantly.

Qualifications

• 3-6 years of experience in data science or related field, particularly in demand forecasting.
• Strong skills in data analysis, visualization, and utilizing pre-trained ML models.
• Ability to communicate insights clearly to non-technical stakeholders.

Responsibilities

• Conduct in-depth data analysis to identify trends and anomalies in demand forecasting.
• Optimize performance of existing forecasting models based on data insights.
• Interpret model results and communicate findings to business stakeholders.
• Develop actionable insights to guide business decisions for accurate forecasting outcomes.
• Collaborate with cross-functional teams to align forecasting outputs with business objectives.
• Identify opportunities for continuous improvement of model performance.

Skills

Data analysis

Data visualization

Python

SQL

Business problem solving

Communication

Attention to detail

Education

Bachelor’s or Master’s degree in Data Science, Statistics, or Computer Science

Job description

At Valiance, we empower businesses with AI-driven insights and data analytics solutions. Specializing in demand forecasting within retail Industry specific to Apparel and Footwear, CPG domains, we leverage standardized ML models to deliver accurate forecasting outcomes to our clients. We are looking for a skilled Data Scientist who can interpret and improve these models to drive real-world business results.

Role Overview:

The Data Scientist will be responsible for applying our pre‑trained demand forecasting models to generate actionable insights and highly accurate forecasting outcomes. This role involves thorough data analysis, identifying trends and anomalies, interpreting results, and communicating findings effectively to a non‑technical business audience. The ideal candidate is less focused on creating algorithms and more oriented towards solving business challenges and providing insights that make a tangible impact.

Key Responsibilities:

• Data Analysis: Conduct in-depth data analysis to identify trends, patterns, and anomalies in demand/Timeseries forecasting for Retail Industry.
• Model Utilization: Leverage existing pre‑trained forecasting models, optimizing their performance by incorporating a nuanced understanding of data points and improving model outcomes based on data insights.
• Interpretation & Communication: Interpret model results and explain outcomes in simple, actionable terms for business stakeholders, ensuring clarity and relevance.
• Insights Generation: Develop insights that guide business decisions, aiming for highly accurate forecasting outcomes to meet business requirements.
• Collaboration: Work closely with cross‑functional teams, including business stakeholders and analysts, to ensure forecasting outputs align with business objectives and provide real‑world value.
• Continuous Improvement: Identify opportunities to improve model performance through better data usage and fine‑tuning, rather than new model development.

Required Skills & Qualifications:

• Experience: 3-6 years of experience in data science or a related field, specifically in Demand/Timeseries forecasting for Retail Industry
• Technical Proficiency: Strong skills in data analysis, data visualization, and working with pre‑trained ML models. Proficiency in Python, and SQL is preferred.
• Business Focus: Strong orientation towards solving business problems rather than a pure focus on machine learning algorithms.
• Communication Skills: Ability to clearly communicate insights and forecast results to non‑technical stakeholders in simple, understandable language.
• Problem Solving: Demonstrated ability to interpret data, uncover actionable insights, and suggest practical solutions for business needs.
• Detail‑Oriented: Thorough attention to detail, ensuring accuracy in forecasting and relevance of insights.
• Educational Background: Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or a related field.