Data Scientist at HP

Apply for the Senior Data Scientist position at HP in Chennai. Lead data science teams, architect predictive models, and build big data pipelines using Python, SQL, AWS, and Apache Spark.

About the Company: HP

HP is a global technology pioneer that reimagines engineering across personal computing, digital printing, and advanced corporate workflows. Operating on the principle that innovation should constantly reinvent the human experience, HP manages massive global supply chains, product telemetry lines, and digital commerce infrastructures that generate billions of data points daily.

The Advanced Data Science & Analytics Division at HP serves as the central brain for translating complex, unstructured enterprise datasets into real-world business strategy. Based in the major technology hub of Chennai, Tamil Nadu, this team is responsible for engineering production-grade machine learning models, deploying cloud-scale AI architectures, and driving process automation. They convert massive datasets into structured intelligence, directly impacting global product development, customer centricity, and multi-market organizational performance.

About the Role: Data Scientist (Senior/Lead Track)

Are you a seasoned data science practitioner who excels at writing production-grade algorithms, testing model assumptions, and leading technical squads? HP is hiring a full-time, permanent Data Scientist to join its elite analytics group in Chennai, Tamil Nadu. This senior-tier, impact-oriented position is designed for professionals holding a quantitative degree who bring 7 to 10 years of deep corporate experience in statistical modeling, machine learning, and big data architectures.

As a Data Scientist at HP, you will step out of simple descriptive tracking to oversee the end-to-end data science lifecycle across multiple business lines. This role bridges the gap between hands-on engineering and technical project leadership. You will architect predictive and prescriptive models of moderate to high complexity, establish automated cleansing programs for disparate big data sources, and partner directly with data engineering teams to build robust cloud pipelines. In addition to technical execution, you will act as a project leader—providing direction, mentoring junior staff, and translating complex mathematical discoveries into clear visual narratives for cross-functional corporate stakeholders.

Key Responsibilities & Advanced Data Science Workflows

• Predictive & Prescriptive Modelling: Design, develop, and deploy machine learning and statistical models to surface hidden trends, predict operational outcomes, and drive innovative business actions.

• Big Data Integration & Cleansing: Develop automated programs and algorithms to ingest, cleanse, integrate, and evaluate massive, unstructured datasets from multiple disparate sources.

• Technical Project Leadership: Lead dedicated project teams of data science professionals, providing structured technical guidance, training, and mentorship to less experienced staff members.

• Data Pipeline Architecture: Partner actively with cross-functional data engineering squads to design reliable data pipelines, improve core data assets, and optimise underlying metrics.

• Model Fine-Tuning & Evaluation: Identify and recommend systematic improvements to existing methodologies by developing new data sources, testing model assumptions, and fine-tuning hyperparameters.

• Cross-Functional Stakeholder Storytelling: Create high-impact visualizations and clear technical narratives within Power BI to effectively present insights to both technical and non-technical corporate audiences.

• Domain Representation: Represent the data science team throughout all development phases of larger, highly complex cross-organizational projects.

Candidate Prerequisites & Key Technical Skills

Successful candidates must combine a rigorous mathematical and statistical foundation with the leadership agility required to steer multi-disciplinary technology teams.

Required Experience & Educational Baseline:

• Professional Tenure: Typically 7 to 10 years of corporate work experience in data analytics, statistical modeling, machine learning, or a related field (or an advanced Graduate Degree with 4 to 7 years of core experience).

• Academic Credentials: Four-year Bachelor’s or Graduate Degree in Mathematics, Statistics, Economics, Computer Science, Data Science, or a related highly quantitative discipline.

• Core Competencies: Exceptional learning agility, strong results orientation, customer centricity, and a proven ability to act as a team or project leader facilitating group decisions.

Core Technical Stack Competencies:

• Data Science Programming: Advanced, professional-level fluency in Python and R for data mining, data manipulation, and algorithmic development.

• Database Engineering (SQL): Strong capability to write complex queries to extract, clean, and join information across large-scale relational databases.

• Cloud & Big Data Infrastructure: Practical, working familiarity with cloud services—specifically Amazon Web Services (AWS)—and distributed computing frameworks like Apache Spark.

• Machine Learning & AI: Foundational and practical knowledge across algorithms, statistical modeling, deep learning, and Natural Language Processing (NLP).

• Business Intelligence (BI): Hands-on experience building clear, automated dashboard visuals using Power BI to communicate model performance.

• Preferred Certifications: Professional programming language certifications (SQL, Python, or data science equivalents) are highly desirable.

Core Position Specifications

• Position Title: Data Scientist (Senior / Lead Track)

• Hiring Organization: HP (Hewlett-Packard)

• Corporate Work Location: Chennai, Tamil Nadu, India

• Experience Allotment: 7 – 10 Years (4 – 7 Years with an Advanced Degree)

• Employment Framework: Full-Time, Permanent corporate assignment

• Complexity Level: Moderately complex to high-impact enterprise issues

• Industry Placement: Technology / Consumer Electronics / Information Technology

• Functional Department: Advanced Data Science & Cross-Org Analytics