{"id":1317212,"url":"https://alion.io/job/puma-energy-senior-data-scientist-builder","title":"Senior Data Scientist – Builder","company":{"id":1887714,"name":"Puma Energy","domain":"pumaenergy.com","url":"https://alion.io/company/pumaenergy","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":80,"open_postings":7,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":19,"computed_at":"2026-10-15T05:46:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Mumbai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":21000,"max_usd":42000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":59},"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Databricks","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Machine Learning","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"A/B Testing","optional":true},{"name":"Agentic Workflows","optional":true},{"name":"Airflow","optional":true},{"name":"CI/CD","optional":true},{"name":"Git","optional":true},{"name":"MLFlow","optional":true},{"name":"Plotly","optional":true},{"name":"Power BI","optional":true},{"name":"Prefect","optional":true},{"name":"PyTorch","optional":true},{"name":"Scikit-learn","optional":true},{"name":"Tableau","optional":true},{"name":"TensorFlow","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-07-27T00:00:00Z","employer_posted_date":"2026-07-27","last_verified_at":"2026-10-15T06:04:24Z","board_verified":true,"closed_at":null,"days_open":80,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":80},"description":"About Puma Energy\nAt Puma Energy, data is at the core of how we transform our global operations and deliver value across the energy value chain. Our Data & Analytics team is building a modern cloud-native data platform on AWS and Databricks, enabling trusted, scalable data products that power analytics, AI, and business-critical decision making.\nWe are looking for a Senior Data Scientist who is fundamentally a builder - someone who personally designs, ships, and owns machine learning and agentic automation systems in production, and who also raises the technical bar for the wider team through hands-on mentorship and sound methodology. This is not a purely strategic or advisory role: you will be in the code, in the data, and in the model - while also guiding other data scientists and engineers on the right approach to take. You will partner closely with our Data Engineering function (which builds our scalable data products on Databricks/AWS/Spark) and with commercial, retail, supply, and trading stakeholders.\nThis role goes beyond model-building in a notebook. You will:\nOwn data science products end-to-end - from framing an ambiguous business problem to shipping and monitoring a production model.\nBuild and deploy applied agentic automation solutions that augment or replace manual analytical/operational workflows.\nGuide teams on the right technical approach - modeling technique, architecture, and productionization strategy - without taking on formal people management.\nPartner with business stakeholders to translate complex problems into scalable, measurable data science and automation solutions.\nContinuously raise the bar on experimentation rigor, reproducibility, and production discipline across the team.\nResponsibilities\nBuild & Ship Production Data Science\nDesign, build, and maintain machine learning models and data science solutions using Databricks, Spark (PySpark), Python, SQL, and AWS.\nOwn the full ML lifecycle: problem framing, data preparation, feature engineering, model training and evaluation, deployment, monitoring, and retraining.\nBuild reusable modeling frameworks, curated feature sets, and self-service data science assets for forecasting, optimization, segmentation, and predictive use cases.\nWrite clean, maintainable, production-grade code with strong testing, version control, and code-review discipline.\nApplied Agentic Automation\nDesign and build applied agentic automation workflows (e.g., LLM/agent-based systems that plan, retrieve, reason, and take action) to automate analytical, operational, or reporting processes.\nEvaluate and select appropriate agentic frameworks and tooling, balancing reliability, cost, and maintainability for production use.\nEstablish guardrails, evaluation, and monitoring practices for agentic systems deployed into business workflows.\nSolution Design & Technical Guidance\nPartner with business stakeholders to understand requirements and translate them into scalable data science and automation solutions.\nGuide and mentor other data scientists and engineers through design reviews, pairing, and code/methodology review - setting the technical direction without formal management authority.\nEvaluate architectural and modeling trade-offs and influence the team's technical standards and best practices.\nDrive solution design from concept through production deployment.\nEngineering Excellence\nBuild production-grade solutions with a strong focus on quality, testing, observability, and reliability.\nImplement automated model validation, monitoring, and retraining pipelines in partnership with Data Engineering and MLOps.\nTroubleshoot production issues and continuously improve model performance and developer experience.\nBusiness Partnership\nCollaborate with business stakeholders, product owners, analysts, architects, and engineers to solve high-impact business problems.\nCommunicate technical concepts and results clearly to technical and non-technical audiences.\nTake end-to-end ownership of solutions from discovery and design to production support.\nRequired Skills & Qualifications\nCore Technical Skills\n6-10 years of hands-on experience in Data Science / Machine Learning, with a proven track record of building, deploying, and maintaining ML solutions in production - not solely prototyping or advisory work.\nStrong, demonstrable hands-on experience with Databricks is essential for this role - this is a non-negotiable requirement, not a nice-to-have.\nAt least 1 year of hands-on experience building applied agentic automation solutions (e.g., LLM agents, agentic workflows, tool-using AI systems) that have been deployed or piloted in a real business context.\nStrong expertise in Python, SQL, and at least one ML framework (TensorFlow, PyTorch, or scikit-learn).\nHands-on experience with Apache Spark (PySpark) and cloud-native data platforms on AWS.\nStrong understanding of the end-to-end ML lifecycle: experimentation, validation, deployment, and monitoring at scale.\nStrong software engineering fundamentals including Git, CI/CD, testing, and code quality.\nExcellent communication skills with the ability to influence stakeholders, mentor peers, and drive technical discussions - without requiring formal people-management experience.\nNice to Have\nDatabricks or AWS Certifications.\nExperience with MLOps tooling (MLflow, Airflow/Prefect) and Infrastructure as Code (Terraform).\nExperience with experimentation / causal inference and A/B testing methodology.\nDomain exposure to energy, commodities, downstream fuel/retail, or trading analytics.\nData visualization skills (Power BI, Tableau, Plotly/Dash).\nWhat Success Looks Like\nOwn and deliver production-grade data science and agentic automation solutions powering business-critical decisions.\nEnable at least one applied agentic automation workflow that measurably reduces manual effort or improves decision speed.\nVisibly raise the technical bar of the team through mentorship, design reviews, and best practices - while remaining hands-on.\nBuild strong partnerships with business stakeholders and deliver measurable business outcomes.\nContinuously improve model reliability, scalability, and cost efficiency on the Databricks/AWS platform.\nWhy Join Puma Energy\nBuild on a modern AWS + Databricks Lakehouse platform used across a global enterprise.\nWork on challenging, high-impact data science and agentic automation problems with real business impact.\nOwn solutions end-to-end with autonomy and accountability - a hands-on builder role, not a purely strategic one.\nGrow your career through technical leadership and mentorship, on an individual-contributor track, without being forced into people management.","description_format":"text","description_chars":6664,"description_truncated":false,"requirements":{"experience_years_min":6,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Energy & Utilities"],"lifecycle":[{"event":"open","at":"2026-09-26T19:42:30Z"}],"visa":[],"liveness":{"score":11,"band":"cold","label":"Long shot","p_open":1,"p_active":0.39,"p_room":0.28,"age_days":80,"expected_fill_days":19,"reasons":["conf:19","win:tail","crowd:"],"computed_at":"2026-10-15T05:46:00Z"},"pay":null,"html_url":"https://alion.io/job/puma-energy-senior-data-scientist-builder","json_url":"https://alion.io/job/puma-energy-senior-data-scientist-builder.json","meta":{"generated_at":"2026-10-15T12:23:59Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":19107,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-16T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":1887714},"rest":"https://alion.io/mcp/rest/get_company?id=1887714"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fpuma-energy-senior-data-scientist-builder"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fpuma-energy-senior-data-scientist-builder"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fpuma-energy-senior-data-scientist-builder"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/puma-energy-senior-data-scientist-builder\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fpuma-energy-senior-data-scientist-builder"}]}