{"id":3464446,"url":"https://alion.io/job/hcltech-senior-data-scientist-ml-python-9","title":"Senior Data Scientist - ML, Python","company":{"id":225,"name":"HCLTech","domain":"hcltech.com","url":"https://alion.io/company/hcltech","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Noida, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":20000,"max_usd":42000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":41},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"Apache Kafka","optional":false},{"name":"Hadoop","optional":false},{"name":"LightGBM","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"NLTK","optional":false},{"name":"NumPy","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Statsmodels","optional":false},{"name":"TensorFlow","optional":false},{"name":"Time Series","optional":false},{"name":"XGBoost","optional":false}],"status":"live","first_seen_at":"2026-10-29T14:57:36Z","employer_posted_date":"2026-10-29","last_verified_at":"2026-10-31T12:16:29Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Job Summary\nThe Senior Data Scientist plays a crucial role in transforming unstructured big data into actionable insights through advanced algorithms and innovative data models. This position is essential for developing strategies that enhance client service delivery and product optimization, using cutting-edge machine learning tools and techniques to drive data-driven decision-making within the organization.\nKey Responsibilities\n1. Design And Implement Advanced Machine Learning Algorithms Using Tensorflow And Pytorch To Extract Insights From Large Datasets, Delivering Customized Analytical Reports Tailored To The Needs Of Colleagues, Clients, And Stakeholders.\n2. Leverage Python And Sql To Develop And Optimize Data Models That Address Specific Organizational Challenges, Ensuring Effective Integration And Management Of Data.\n3. Analyze And Mine Large Datasets To Identify Trends And Patterns, Utilizing Advanced Analytics Techniques To Interpret Findings And Provide Actionable Recommendations Based On Experimental Results.\n4. Collaborate With Cross-Functional Teams To Identify Opportunities For Utilizing Data Insights To Formulate Strategic Business Solutions That Enhance Operational Efficiency And Product Offerings.\n5. Create Comprehensive Visualizations And Reports Using Data Visualization Tools To Communicate Complex Analysis And Results Clearly, Enabling Informed Decision-Making For Customers And Stakeholders.\nSkill Requirements\n\nSkill Matrix\n\nDS/ML (E2Band)\n\nYears of Exp\nTEX:6+yrs; REX: 5+yrs\n\nLocation - Pan India or any constraint - Also mention location for physical attendance\nNoida, Bangalore, Hyd, Chennai\n\nProject type (Support / Dev / Maintenance / Testing)\nDev\n\nTeam Handling / Individual Contributor\nBoth\n\nShift involved - If yes please share timing.\nNo\n\nCustomer interview involved - yes / No\nNo\n\nSell Rate\nNA\n\nNotice Period\nP1:0-30days; P2: 30-45days: P3: 45-90days\n\nSkill\nMandatory\nProficiency Level (1-5)\n\nMachine Learning & NLP\nYes\n5\n\nPython\nYes\n5\n\nNatural Language Processing [NLP],\nYes\n5\n\nMachine learning model evaluation\nYes\n5\n\nKafka,Apache Spark\nYes\n5\n\nNumPy, pandas, scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, NLTK, SpaCy, StatsModels,Cross-validation, ROC/AUC, Precision/Recall, F1-score, Confusion Matrix,Supervised/Unsupervised Learning, Deep Learning, Time Series, Reinforcement Learning,Hadoop, Apache Kafka, Apache Airflow\nGood to Have\n4\n\nOther Requirements\n1. 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