{"id":803382,"url":"https://alion.io/job/loandna-data-scientist","title":"Data Scientist","company":{"id":674779,"name":"loanDNA","domain":"loandna.com","url":"https://alion.io/company/loandna","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Rippling","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Chennai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":18000,"max_usd":49000,"period":"year","method":"role_country_seniority_unknown","sample_n":120},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"CatBoost","optional":true},{"name":"CI/CD","optional":true},{"name":"Databricks","optional":true},{"name":"Docker","optional":true},{"name":"FastAPI","optional":true},{"name":"GCP","optional":true},{"name":"Git","optional":true},{"name":"Interpretability","optional":true},{"name":"Kubernetes","optional":true},{"name":"LightGBM","optional":true},{"name":"MLFlow","optional":true},{"name":"NumPy","optional":true},{"name":"Pandas","optional":true},{"name":"pySpark","optional":true},{"name":"Python","optional":true},{"name":"PyTorch","optional":true},{"name":"Rest API","optional":true},{"name":"Scikit-learn","optional":true},{"name":"SHAP","optional":true},{"name":"Snowflake","optional":true},{"name":"Spark","optional":true},{"name":"SQL","optional":true},{"name":"TensorFlow","optional":true},{"name":"XGBoost","optional":true}],"status":"live","first_seen_at":"2026-07-31T10:50:05Z","employer_posted_date":"2026-07-31","last_verified_at":"2026-10-03T00:52:53Z","board_verified":true,"closed_at":null,"days_open":63,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":63},"description":"At loanDNA, we believe great leadership starts with the right people. Our team is built on industry veterans and forward-thinkers who bring a powerful mix of mortgage expertise, technical skills, and a passion for innovation.\nWe hire leaders who understand the complexities of the mortgage and financial services industry and embrace emerging technologies-AI, automation, and advanced analytics-to deliver smarter, faster solutions for our clients.\nFrom evaluating loan quality and collateral to shaping disposition strategies and optimizing performance, our leadership team combines hands-on experience with cutting-edge insight. Their perspective spans the full mortgage lifecycle, ensuring clients benefit from strategies that are both practical today and built for tomorrow.\nExperience - 5 to 10 years\nWork Location - Chennai\nWork Mode- Work from Office\nAbout the Role\nWe are looking for an experienced Data Scientist to join our team and help build the next generation of data-driven solutions for the mortgage and real estate industry.\nIn this role, you will work at the intersection of data science, machine learning, cloud technology, and large-scale data engineering. You will have the opportunity to take ownership of complex analytical problems, develop production-grade machine learning solutions, and work with large volumes of mortgage, property, valuation, market, and transactional data.\nYou will work closely with Data Engineering, Product, Technology, Analytics, and Business teams to turn complex business problems into scalable data science solutions.\nMortgage domain experience is preferred but not required. We are equally interested in candidates with strong data science fundamentals who are excited to learn the mortgage and real estate domain.\nWho You Are\nYou are a hands-on Data Scientist who enjoys solving complex problems with data.\nYou are comfortable working across the complete machine learning lifecycle - from understanding raw data and identifying patterns to feature engineering, model development, validation, deployment, and production monitoring.\nYou are someone who can move between experimentation and production. You are equally comfortable writing Python to build a model, SQL to analyse hundreds of millions of records, and collaborating with engineers to operationalise a solution.\nYou enjoy understanding the business problem behind the model and are able to communicate technical findings clearly to both technical and non-technical stakeholders.\nMost importantly, you are curious, analytical, and comfortable working in an environment where you are expected to explore, experiment, challenge assumptions, and continuously improve existing solutions.\nWhat You’ll Do\nAs a Data Scientist, you will:\nDesign, develop, and productionise machine learning and statistical models.\nWork with large-scale structured and unstructured datasets.\nPerform exploratory data analysis to identify patterns, trends, anomalies, and opportunities.\nDevelop advanced feature engineering and data transformation pipelines.\nBuild predictive models using techniques such as regression, tree-based models, gradient boosting, ensemble modelling, clustering, ranking, and deep learning where appropriate.\nDevelop end-to-end ML pipelines covering data preparation, training, validation, deployment, scoring, and monitoring.\nConduct model backtesting, benchmarking, hyperparameter optimisation, and performance analysis.\nDevelop model explainability and interpretability using techniques such as SHAP and feature importance.\nMonitor model performance, data drift, feature drift, stability, coverage, and production accuracy.\nDevelop scalable batch and real-time prediction pipelines.\nBuild reusable analytical frameworks rather than one-off solutions.\nDesign automated data-quality and model-quality checks.\nInvestigate production issues and perform root-cause analysis.\nIdentify opportunities to improve existing models, data pipelines, and analytical methodologies.\nWork closely with Data Engineers and Software Engineers to move models from experimentation into production.\nTranslate business problems into measurable data science objectives.\nPresent model results, insights, recommendations, and trade-offs to business stakeholders and leadership.\nTechnology You’ll Work With\nOur environment includes modern cloud, data, and machine learning technologies.\nYou may work with:\nData & Cloud Platforms\nSnowflake\nDatabricks\nAWS\nMicrosoft Azure\nGoogle Cloud Platform\nProgramming & Data\nPython\nSQL\nPySpark\nPandas\nNumPy\nMachine Learning\nScikit-learn\nXGBoost\nLightGBM\nCatBoost\nMLflow\nSHAP\nTensorFlow / PyTorch\nEngineering & MLOps\nGit\nDocker\nKubernetes\nREST APIs\nFastAPI\nCI/CD\nModel registries\nAutomated ML pipelines\nCloud-based model deployment and monitoring\nYou do not need experience with every technology listed above. We value strong fundamentals and the ability to learn new technologies quickly.\nWhat We’re Looking For\nRequired\nBachelor's or master’s degree in data science, Computer Science, Statistics, Mathematics, Engineering, Economics, or another quantitative discipline.\nStrong professional experience in Data Science, Machine Learning, Advanced Analytics, or a related field.\nStrong proficiency in Python and SQL.\nStrong understanding of machine learning and statistical modelling.\nExperience developing predictive models using real-world datasets.\nExperience with feature engineering, model evaluation, and model optimisation.\nExperience working with large and complex datasets.\nStrong understanding of model validation and performance metrics.\nAbility to translate business requirements into analytical and machine learning solutions.\nStrong problem-solving and analytical skills.\nAbility to communicate complex technical concepts to different audiences.\nWhat You’ll Get\nThis role provides the opportunity to:\nWork on complex, real-world machine learning problems with measurable business impact.\nBuild models using large-scale mortgage and real estate datasets.\nWork with modern cloud and data platforms such as Snowflake and Databricks.\nOwn solutions across the complete machine learning lifecycle.\nBuild production systems rather than proof-of-concept models alone.\nExperiment with traditional machine learning, advanced analytics, and Generative AI.\nCollaborate with experienced Data Scientists, Engineers, Product teams, and domain experts.\nInfluence the architecture and direction of data science solutions.\nContinuously learn new technologies and modelling techniques.\nSee your models and analytical solutions directly influence products and business decisions.\nIf you are passionate about applying data science, machine learning, cloud technologies, and AI to real-world problems, we would love to hear from you.","description_format":"text","description_chars":6749,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Real Estate","Financial Software & Embedded Finance","Mortgage Lending & Brokers"],"lifecycle":[{"event":"open","at":"2026-09-12T08:43:04Z"}],"liveness":{"score":9,"band":"cold","label":"Long shot","p_open":1,"p_active":0.33,"p_room":0.28,"age_days":62,"expected_fill_days":21,"reasons":["conf:17","win:tail","crowd:"],"computed_at":"2026-10-02T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/loandna-data-scientist","json_url":"https://alion.io/job/loandna-data-scientist.json","meta":{"generated_at":"2026-10-03T01:48:44Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":1810,"day_limit":5000,"remaining_today":3190,"minute_limit":60,"resets_at":"2026-10-04T00:00:00Z"}}}